Luminosity and Chromaticity: On Light and Color

Luminosity and Chromaticity: On Light and Color

Key Terms and Ideas

  • Luminosity and Chromaticity
  • Light and Color
  • Diwali (Festival of Light) and Holi (Festival of Colors)
  • Rama and Krishna
  • Non Dual Vedanta and Trika Philosophy
  • 1 and 3
  • Verticalism and Horizontalism
  • Vedic and Tantric
  • Flute of Krishna and Shiva Jyotir Linga
  • Bow and Arrow of Ram
  • Ram Parivar and Shiv Parivar
  • Shiv Ratri
  • Plato and Aristotle
  • Sun, Moon, Earth and Mars
  • Rods and Cones in Retina
  • Color Temperature
  • Lok and Kosh
  • Seven Chakra
  • Trishool
  • Ram, Lakshman, Sita, Hanuman
  • Achromatic and Chromatic
  • Grey scale and Color Primaries
  • Mind and Moon
  • Moon and Emotions
  • Tone Circle
  • Color Circle
  • Pythagoras
  • 3 and 7
  • 137
  • 007
  • Prism
  • Seven Colors
  • 4 + 3 = 7
  • 4 x 3 = 12
  • Pentatonic
  • Heptatonic
  • Diatonic Scale
  • Chromatic Scale

Newton’s Color Circle

Source: http://winlab.rutgers.edu/~trappe/Courses/ImageVideoS06/MollonColorScience.pdf

Color Circle in Opticks of I.Newton

Source: Reprint of Opticks by Project Gutenberg

Color Sensation

Source: Understanding color & the in-camera image processing pipeline for computer vision

Electromagnetic Spectrum

Source: Notes for the course of Color Digital Image Processing

Color Temperature

Source: Understanding color & the in-camera image processing pipeline for computer vision

Color Temperatures of the Stars

Luminosity Function

Source: Understanding color & the in-camera image processing pipeline for computer vision

CIE 1931 XYZ

Source: Understanding color & the in-camera image processing pipeline for computer vision

Luminance

Source: Human Vision and Color

Brightness, Lightness,Hue, Saturation, and Luminosity

Source: The Brightness of Colour

Brightness has been defined as the perceived intensity of a visual stimulus, irrespective of its source. Lightness, on the other hand, is defined as the apparent brightness of an object relative to the object’s reflectance. Thus increasing the intensity of light falling on an object will increase its apparent brightness but not necessarily its apparent lightness, other things being equal [1]. Saturation is a measure of the spectral ‘‘purity’’ of a colour, and thus how different it is from a neutral, achromatic stimulus. Hue is the perception of how similar a stimulus is to red, green, blue etc. Luminous efficiency, or luminosity, measures the effect that light of different wavelengths has on the human visual system. It is a function of wavelength, usually written as V(l) [2], and is typically measured by rapidly alternating a pair of stimuli falling on the same area of the retina; the subject alters the physical radiance of one stimulus until the apparent flickering is minimised. Thus luminance is a measure of the intensity of a stimulus given the sensitivity of the human visual system, and so is integrated over wavelength [3]. Luminance is thought to be used by the brain to process motion, form and texture [4].

Clearly, brightness is monotonically related to luminance in the simplest case: the more luminant the stimulus is, the brighter it appears to be. However, the Helmholtz-Kohlrausch (HK) effect shows that the brightness of a stimulus is not a simple representation of luminance, since the brightness of equally luminant stimuli changes with their relative saturation (i.e. strongly coloured stimuli appear brighter than grey stimuli), and with shifts in the spectral distribution of the stimulus (e.g. ‘blues’ and ‘reds’ appear brighter than ‘greens’ and ‘yellows’ at equiluminance) [1; 5–6].

The HK effect has been measured in a variety of psychophysical studies [7–8] and is often expressed in terms of the (variable) ratio between brightness and luminance. 

Chromaticity

Source: Human Vision and Color

Human Eye

Source: Human Vision and Color

Human Retina

Source: Human Vision and Color

Rods and Cones Photoreceptors

Source: Human Vision and Color

Color Receptors

Source: Human Vision and Color

Tristimulus Color

Source: Color/CMU

Visual Sensitivity

Source: Human Vision https://people.cs.umass.edu/~elm/Teaching/ppt/691a/CV%20UNIT%20Light/691A_UNIT_Light_1.ppt.pdf

Light and Color (Photometry and Colorimetry) I

Source: Interactive Computer Graphics/UOMichigan

Light and Color (Photometry and Colorimetry) II

Source: Interactive Computer Graphics/UOMichigan

Two Types of Light Sensitive Cells

Source: Interactive Computer Graphics/UOMichigan

Cones and Rod Sensitivity

Source: Interactive Computer Graphics/UOMichigan

Distribution of Cones in Retina

Source: DIVERSE CELL TYPES, CIRCUITS, AND MECHANISMS FOR COLOR VISION IN THE VERTEBRATE RETINA

Types of Color Stimuli

Source: Perceiving Color. https://www.ics.uci.edu/~majumder/vispercep/chap5notes.pdf

Color Perception

Source: Perceiving Color. https://www.ics.uci.edu/~majumder/vispercep/chap5notes.pdf

CIE XYZ Model

Source: Human Vision and Color

Luminance and Chromaticity Space

Source: Understanding color & the in-camera image processing pipeline for computer vision

1931 CIE Chromaticity Chart

CIE 1931 Chromaticity Diagram

Source: Human Vision and Color

Source: Notes for the course of Color Digital Image Processing

Additive Colors

Source: Human Vision and Color

Subtractive Colors

Source: Human Vision and Color

Color Mixing

Source: Human Vision and Color

Color Appearance Models
  • RGB
  • CMY
  • CIE XYZ
  • CIE xyY
  • CIE LAB
  • Hunter LAB
  • CIE LUV
  • CIE LCH
  • HSB
  • HSV
  • HSL
  • HSI
  • YIQ for NTSC TVs in USA
  • YUV for PAL TVs in EU
  • YCbCr for digital TVs
  • Munsell Color System

Color Models are device independent. For discussion of device dependent color spaces, please see my post Digital Color and Imaging.

LMS, RGB, and CIE XYZ Color Spaces

Source: Color/CMU

HSV Color Space

My Related Posts

Reflective Display Technology: Using Pigments and Structural Colors

Color Science and Technology in LCD and LED Displays

Color Science of Gem Stones

Nature’s Fantastical Palette: Color From Structure

Optics of Metallic and Pearlescent Colors

Color Change: In Biology and Smart Pigments Technology

Color and Imaging in Digital Video and Cinema

Digital Color and Imaging

On Luminescence: Fluorescence, Phosphorescence, and Bioluminescence

On Light, Vision, Appearance, Color and Imaging

Understanding Rasa: Yoga of Nine Emotions

Shapes and Patterns in Nature

Key Sources of Research

What Are The Characteristics Of Color?

https://www.pantone.com/articles/color-fundamentals/what-are-the-characteristics-of-color

Birren Color Theory

by ADMIN on MARCH 11, 2012

http://www.wonderfulcolors.org/blog/birren-color-theory/

Light, Color, Perception, and Color Space Theory

Professor Brian A. Barsky

barsky@cs.berkeley.edu

Computer Science Division
Department of Electrical Engineering and Computer Sciences University of California, Berkeley

Understanding Color Spaces and Color Space Conversion

https://www.mathworks.com/help/images/understanding-color-spaces-and-color-space-conversion.html

The Human Visual System and Color Models

Click to access Carmody_Visual&ColorModels.pdf

Defining and Communicating Color: The CIELAB System

Color Vision and Arts

http://www.webexhibits.org/colorart/index.html

PRECISE COLOR COMMUNICATION: COLOR CONTROL FROM PERCEPTION TO INSTRUMENTATION

KonicaMinolta

A short history of color theory

https://programmingdesignsystems.com/color/a-short-history-of-color-theory/index.html

Let’s Colormath

Understanding the formulas of color conversion

https://donatbalipapp.medium.com/colours-maths-90346fb5abda

A History of Human Color Vision—from Newton to Maxwell

Barry R. Masters

Optics and Photonics January 2011

https://www.osa-opn.org/home/articles/volume_22/issue_1/features/a_history_of_human_color_vision—from_newton_to_max/

The Difference Between Chroma and Saturation

Munsell Color

Charles S. Peirce’s Phenomenology: Analysis and Consciousness

By Richard Kenneth Atkins

The Evolution of Human Color Vision/ Jeremy Nathans

Jeremy Nathans Lecture on Color Vision

JEREMY NATHANS LECTURE ON COLOR VISION

JEREMY NATHANS LECTURE ON COLOR VISION

JEREMY NATHANS LECTURE ON COLOR VISION

The Genes for Color Vision

Jeremy Nathans

SCIENTIFIC AMERICAN FEBRUARY 1989

A Short History of Color Photography

Photography  |  Angie Kordic

https://www.widewalls.ch/magazine/color-photography

Blue: The History of a Color (2001)

followed by Black: The History of a Color (2009) and then Green: The History of a Color (2014), all produced by the same publisher. A fifth, devoted to yellow, should come next. 

Historic Look on Color Theory 

Steele R. Stokley

The evolution of colour in design from the 1950s to today

Francesca Valan

Journal of the International Colour Association (2012): 8, 55-60

Greek Color Theory and the Four Elements

J.L. Benson

University of Massachusetts Amherst

A SHORT HISTORY OF COLOUR PHOTOGRAPHY

https://blog.scienceandmediamuseum.org.uk/a-short-history-of-colour-photography/

History of Color System

The Origins of Modern Color Science

J D Mollon

Click to access MollonColorScience.pdf

The History of Colors

Tobias Kiefer

Click to access Assignment_History_of_Colors.PDF

Notes for the course of Color Digital Image Processing

Edoardo Provenzi

Understanding color & the in-camera image processing pipeline for computer vision

Dr. Michael S. Brown

Canada Research Chair Professor York University – Toronto

ICCV 2019 Tutorial – Seoul, Korea

Chapter 2
Basic Color Theory

Click to access t3.pdf

Color Science

CS 4620 Lecture 26

Click to access 26color.pdf

Color Image Perception, Representation and Contrast Enhancement

Yao Wang
Tandon School of Engineering, New York University

A GUIDE TO LIGHT AND COLOUR DEMONSTRATIONS

Arne Valberg, Bjørg Helene Andorsen, Kine Angelo, Barbara Szybinska Matusiak and Claudia Moscoso

Norwegian University of Science and Technology Trondheim, Norway

https://www.ntnu.edu/documents/1272527942/1272817015/2015-09-08+DEMO+web.pdf/f1695ca5-b834-4d05-a011-a185f6562e32

A Primer to Colors in Digital Design

Archit Jha

Jul 16, 2017

https://uxdesign.cc/a-primer-to-colors-in-digital-design-7d16bb33399e

Chapter 7 ADDITIVE COLOR MIXING

Click to access 07_additive-color.pdf

Computergrafik

Matthias Zwicker Universität Bern Herbst 2016

Color

Click to access ColorPerception.pdf

Introduction to Computer Vision

The Perception of Color

In: Webvision: The Organization of the Retina and Visual System [Internet]. Salt Lake City (UT): University of Utah Health Sciences Center; 1995–.2005 May 1 [updated 2007 Jul 9]

https://pubmed.ncbi.nlm.nih.gov/21413396/

Visual Pigment Gene Structure and Expression in Human Retinae 

Tomohiko Yamaguchi,  Arno G. Motulsky,  Samir S. Deeb

Human Molecular Genetics, Volume 6, Issue 7, July 1997, Pages 981–990, https://doi.org/10.1093/hmg/6.7.981

https://academic.oup.com/hmg/article/6/7/981/572151

The Difference Between Chroma and Saturation

LUMINANCE AND CHROMATICITY

https://colorusage.arc.nasa.gov/lum_and_chrom.php

Number by Colors

A Guide to Using Color to Understand Technical Data
  • Brand Fortner
  • Theodore E. Meyer

Chapter 5 Perceiving Color

The Practical Guide To Color Theory For Photographers

History of the Bauhaus

https://bauhaus.netlify.app/form_color/color/

The Digital Artist’s Complete Guide To Mastering Color Theory

byLeigh G

BASIC COLOR THEORY

Anthony Holdsworth

Molecular Genetics of Color Vision and Color Vision Defects

Maureen Neitz, PhDJay Neitz, PhD

Arch Ophthalmol. 2000;118(5):691-700. doi:10.1001/archopht.118.5.691

https://jamanetwork.com/journals/jamaophthalmology/fullarticle/413200

Color Theory: Introduction to Color Theory and the Color Wheel

https://blog.thepapermillstore.com/color-theory-introduction-color-wheel/

Color Spaces and Color Temperature

https://tigoe.github.io/LightProjects/color-spaces-color-temp.html

The Brightness of Colour

David Corney1, John-Dylan Haynes2, Geraint Rees3,4, R. Beau Lotto1*

EECS 487: Interactive Computer Graphics

Colorimetry

KonicaMinolta

Basics of Color Theory

THE BASICS OF COLOR PERCEPTION AND MEASUREMENT

Hunterlab

https://www.hunterlab.com/color-measurement-learning/glossary/

Color Matching and Color Discrimination

The Science of Color

2003

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.457.9467&rep=rep1&type=pdf

1.3 Color Temperature

https://www.mat.univie.ac.at/~kriegl/Skripten/CG/CG.html

https://www.mat.univie.ac.at/~kriegl/Skripten/CG/node10.html

Color Spaces and Color Temperature

https://tigoe.github.io/LightProjects/color-spaces-color-temp.html

Digital Camera Sensor Colorimetry

Douglas A. Kerr

Click to access Sensor_Colorimetry.pdf

Chromatic luminance, colorimetric purity, and optimal aperture‐color stimuli

DOI: 10.1002/col.20356

https://www.researchgate.net/publication/230164581_Chromatic_luminance_colorimetric_purity_and_optimal_aperture-color_stimuli

Title: A Review of RGB Color Spaces …from xyY to R’G’B’

The CIE XYZ and xyY Color Spaces

Douglas A. Kerr

Click to access CIE_XYZ.pdf

DIVERSE CELL TYPES, CIRCUITS, AND MECHANISMS FOR COLOR VISION IN THE VERTEBRATE RETINA

Wallace B. Thoreson and Dennis M. Dacey

Department of Ophthalmology and Visual Sciences, Truhlsen Eye Institute, University of Nebraska Medical Center, Omaha, Nebraska; and Department of Biological Structure, Washington National Primate Research Center, University of Washington, Seattle, Washington

Physiol Rev 99: 1527–1573, 2019 Published May 29, 2019; doi:10.1152/physrev.00027.2018

https://journals.physiology.org/doi/pdf/10.1152/physrev.00027.2018

Human Vision

Introduction to color theory

https://graphics.stanford.edu/courses/cs178-10/applets/locus.html

COLOR WHEELS

https://www2.bellevuecollege.edu/artshum/materials/art/tanzi/Winter04/111/111CLRWHLSW04.htm

Human Vision and Color

UT

Click to access 121.pdf

COLOR VISION MECHANISMS

Andrew Stockman

Department of Visual Neuroscience UCL Institute of Opthalmology London, United KIngdom

David H. Brainard

Department of Psychology University of Pennsylvania Philadelphia, Pennsylvania

Color

CMU

Click to access lecture15.pdf

What Are The Characteristics Of Color?

Pantone

https://www.pantone.com/articles/color-fundamentals/what-are-the-characteristics-of-color

A Guide to Color


Guide C-316
Revised by Jennah McKinley

https://aces.nmsu.edu/pubs/_c/C316/welcome.html

A History of Color

The Evolution of Theories of Lights and Color
  • Robert A. Crone

https://link.springer.com/book/10.1007/978-94-007-0870-9

The Brilliant History of Color in Art

Victoria Finlay

A History of Light and Colour Measurement
Science in the Shadows

Sean F Johnston

University of Glasgow, Crichton Campus, UK

Color codes: modern theories of color in philosophy, painting and architecture, literature, music and psychology

Charles Riley

Chapter 6 Colour

History of Color Systems

Color and Imaging in Digital Video and Cinema

Color reproduction and management is a key task in digital video and cinema production. Choices of hardware, software, and handoffs and handshakes in production process require control over color of an image or a video. This is a very complex task due to several reasons.

  • Complexity of Color and its measurement
  • Changing color and light conditions during shoot indoors and outdoors
  • Hardware and software encoded color standards are inconsistent. Cameras, displays and projectors all have different color specifications.
  • After shoot, the data recorded is processed using different softwares for editing, grading, compositing, CG rendering, animations, and special effects. These softwares require different data formats (Log vs Linear).
  • After processing video data is required to meet different deliverables in multiple formats for displays and projectors.
  • Archiving and storage of data requires specific color formats.
  • There are also subjective and artistic requirements to meet look and feel of the data.

My post is to bring these issues to light and to educate. I hope after reading this post you know little more about color and its management during digital video and cinema production.

Key Terms

  • ACES
  • LUT
  • REC709
  • REC2020
  • Color Gamut
  • CIE Chromaticies
  • CIE XYZ
  • ACES 1.1
  • ACES 1.2
  • Color Workflow
  • Premier Pro
  • Final Cut Pro
  • Davinci Resolve
  • Avid Media Composer
  • IDT
  • ODT
  • RRT
  • Maya
  • Nuke
  • After Effects
  • ITU
  • SMPTE
  • AECS
  • ACES AP0
  • ACES AP1
  • BT 709
  • BT 2020
  • BT 2100 in 2016 to include HDR
  • HDR High Dymanic Range
  • HDR 10
  • SLog3
  • Fusion
  • Resolve
  • After Effects
  • OCIO
  • IDT
  • ODT
  • RRT
  • Red
  • Arri
  • Sony
  • Canon
  • Octane
  • CG
  • Linear representation of light
  • Gamma Curve
  • Log Gamma Curve
  • Log Profiles
  • Dynamic Range
  • Linearize work flow
  • Wide Gamut color space
  • Rendering engines
  • VRay
  • Arnold
  • Redshift
  • Octane
  • Cinema 4d
  • Blender
  • EXR linearize
  • Reference Rendering Transform
  • Color Manager OCIO
  • SLog
  • ACES CC
  • ACES CCT
  • Wave Form
  • DaVinci Resolve
  • After Effects
  • FS7
  • Rushes
  • Academy of Motion Picture Arts and Sciences
  • American Society of Cinematographers ASC
  • Digital Cinema Initiatives DCI
  • Society of Motion Picture and Television Engineers SMPTE
  • OpenColor IO
  • 32 bit per channel
  • 8 Bit
  • ACES CG Input
  • REC 709 Output

Human Vision

Source: https://z-fx.nl/ColorspACES.pdf

Color Models of Human Vision

Please see my two previous posts.

On Light, Vision, Appearance, Color and Imaging

Digital Color and Imaging

Digital Color

Source: What is 4K, UHD, SLog3, Rec 2020

The process of capturing and reproducing images requires a collaboration of camera sensors, file formats, rendering technologies, and display or printer technologies. All of these have different ways and different capabilities of representing color and intensity. In addition, they are all different from how our eyes work which further complicates things. As a result, over the years, several standards and processes have been implemented to accomplish this. They all involve some aspects of how to capture and store colors, what range of colors can be dealt with and how to adjust intensity to best reproduce the real world. To understand the new 4k technologies, including SLOG3, HDR, Rec 2020 etc, an understanding of the following is needed.

  • Gamut
  • Bit Depth
  • Gamma
  • Gamma Correction
  • Color spaces

Color Gamut

Source: https://z-fx.nl/ColorspACES.pdf

Color Capture in Digital Video and Cinema

Source: HOW DOES A DIGITAL CAMERA SENSOR WORK?

A modern digital camera’s sensor comes in one of two varieties generally. It will either be a Complementary Metal Oxide Semiconductor (CMOS), or a Charge-Coupled Device (CCD) sensor. The CCD type is mainly used in older models, but is still used on some modern cameras. Each type has its own advantages and disadvantages, but that is a topic for another article.

The most basic way you can understand how a sensor works is when the shutter opens, the sensor captures the photons that hit it and that is converted to an electrical signal that the processor in the camera reads and interprets as colors. This information is then stitched together to form an image. That is insanely over-simplified though.

The more complex answer is that a sensor is made up of millions of cavities called “photosites,” and these photosites open when the shutter opens and close when the exposure is finished (the number of photosites is the same number of pixels your camera has). The photons that hit each photosite are interpreted as an electrical signal that varies in strength based on how many photons were actually captured in the cavity. How precise this process is depends on your camera’s bit depth.

If we looked at a picture that was taken with just that electrical data mentioned earlier from the sensor, then the images would actually be in gray-scale. How we get colored images is by what’s known as a “Bayer filter array.” A Bayer filter is a colored filter placed over-top of each photosite and is used to determine the color of an image based on how the electrical signals from neighboring photosites measure. The colors of the filters are the standard red, green and blue, with a ratio of one red, one blue and two green in every section of four photosites.

Image for post
A graphic of light entering photosites with Bayer filters layered on. (graphic/Cambridge in Colour)

The red filter allows red light to be captured, the blue allows blue light in and the green allows green light in. The light that doesn’t match that photosites filter is reflected. This means that we are losing two-thirds of the light that can be captured and it is only of one color for each photosite. This forces the camera to guess what the amount of the other two colors is in each given pixel.

The data that is interpreted by the sensor with the Bayer filter array is what a RAW image file is.

The camera then goes through a process to estimate how much of each color of light there was for each photosite and colors the image based on that guessing.

Single Sensor Vs Multiple Sensors in Cameras

  • Sensor Type
    • CCD
    • CMOS
  • Sensor Size
    • Full Frame
    • APS-C
  • Sensor Numbers
    • Single – 1 CMOS or 1CCD
    • Multiple – 2CCD, 3CCD, 3CMOS
  • Sensor Pixels
    • 24 MP
    • 48 MP
  • Sensor Dynamic Range
    • Range of brightness sensor captures
    • 14 Stops
    • 20 Stops

A camera sensor can only capture a limited range of light. When a scene extends beyond that range of light, techniques such as filters, flash, and editing techniques can still create a dramatic, well-detailed image.

Comparison of different sensor sizes

Image Source: Camera Sensor Sizes Explained: What You Need to Know

Source: Camera Sensor Sizes Explained: What You Need to Know

Cameras with Single Image Sensor

With CFA Color Filter Array

  • Bayer CFA

Bayer CFA

Source:

Conversion of RAW files

Source: https://z-fx.nl/ColorspACES.pdf

Cameras with multiple Image Sensors

Cameras with multiple sensors do not require Bayer CFA.

  • 3 CCD – Single color info per sensor
  • 3 CMOS – Single color info per sensor
  • 4 CCD – Single color info per sensor plus Near Infra Red (NIR) info

Color Spaces in the Digital Video and Cinema

Image Source: Common Color Spaces

Gamut of Color Spaces

Color Space is characterized based on how much of its gamut covers the CIE Chromaticity Diagram.

Image Source: Why Every Editor, Colorist, and VFX Artist Needs to Understand ACES

Source: The Pointer’s Gamut
The coverage of real surface colors by RGB color spaces and wide gamut displays

Source: The Pointer’s Gamut
The coverage of real surface colors by RGB color spaces and wide gamut displays

Device Dependent Color Spaces

Capture Devices

Professional Cameras for Cinematography and Videography from

  • Sony
  • Canon
  • Arri
  • Red

Camera Sensor Dynamic Range

Image Source: Understanding 4K, Ultra HD and HDR

Conversion of RAW to Video Formats

Image Source: Understanding 4K, Ultra HD and HDR

Sony SLog Transfer Function

Image Source: Understanding 4K, Ultra HD and HDR

Sony Transfer Functions

Image Source: Understanding 4K, Ultra HD and HDR

Other Transfer Functions

Image Source: Understanding 4K, Ultra HD and HDR

Sony Color Spaces

Image Source: Understanding 4K, Ultra HD and HDR

Slog, Gamma, and Gamut

Source: Are S-Log and Color Space separate things?

S-log is a specific gamma, color space is a general term referring to gamuts. A very crude way of thinking is gamma refers to brightness and gamut refers to color.

It’s important to know which gamma and gamut you are recording in as this helps to ensure there is correct gamma and gamut mapping from capture to exhibition.

What is Gamma?

Gamma is also called Tone Mapping.

Source: What is 4K, UHD, SLog3, Rec 2020

Each pixel has a brightness level, which is the average of {red, green, blue} values, and this is called its luminance. In order to reproduce an image from capture to display, the luminance needs to be accurately reproduced. Since sensors and displays can have different luminance characteristics, there needs to be a mapping or relationship between a pixel’s numerical values and the actual luminance…this relationship is called the Gamma.

Linear Space is counter to Gamma Space or Log Space.

Log Space or Gamma Space

Log Curve simulates a non-linear curve. Log Color Profiles can be created for a camera.

  • Arri LogC
  • Cineon Dpx
  • RedLogFilm
  • Canon-Log

Source: LOG COLOR IN-DEPTH

Every professional camera manufacturer and almost every VFX and grading package has a Log workflow. Camera companies such as Arri, Sony, Canon, Red and many others implement their own flavors of Log color space. With the Log workflow it is possible to fit more dynamic range into an image and simulate nonlinear film response to light. The term Log is derived from the word logarithm, which is a fancy name for a function which outputs exponents for the given number.

Log Spaces of Different Brands

Source: LOG COLOR IN-DEPTH

Gamma Curve = Tone Curve = Log Curve

Log footage is an important part of the post-production workflow. Here’s what you need to know.

Source: UNDERSTANDING LOG AND COLOR SPACE IN COMPOSITING

As digital filmmaking becomes more and more affordable, technologies become increasingly available to colorists or post-production professionals. In this case, Log footage. The Log (logarithmic) color space has been around for quite a while. Initially high-end post houses used it with scanned film negatives in a color space called Cineon Log. Now, pretty much all camera manufacturers offer their own Log curve (or multiple). There is S-Log 2&3 (Sony), LogC (Arri), Canon LogV-Log (panasonic), Red LogfilmBlackmagic Log, etc. Each of them are different, usually tailored for the color science of the particular manufacturer’s products.

The biggest reason to use the Log color curve is how it retains the most dynamic range of information from the camera sensor (or film negative). It encodes what the camera sees logarithmically, meaning that the correlation between the exposure of the image (measured in stops) and the recorded image  is completely constant over a wider range. It utilizes more of the sensor’s information than a standard video curve because it’s saving as much data as possible rather than capturing specifically for the human eye or a video screen. This gives you much more color data to work with in post-production.

Linear Space

Source: Color Management/Blender

For correct results, different Color Spaces are needed for rendering, display and storage of images. Rendering and compositing is best done in scene linear color space, which corresponds more closely to nature, and makes computations more physically accurate.

Log Space to Linear Space Conversion

Source: LOG COLOR IN-DEPTH

In conclusion, to bring an image into the log color space all we need to do is to apply a logarithmic function which transforms values of pixels based on the log curves above. To linearize a log picture, we use an exponent function. Since the log color space is a mathematical transformation of values of pixels, it can be used with any types of file format, bit depth and channel. 

White Point

Is the color temperature of light. Outdoors, Indoor, Sunny, Cloudy conditions affect White Point. In Cameras white point can be adjusted depending on light conditions. D65 simulates daylight.

  • D50 – 5000 K
  • D60 – 6000 K
  • D65 – 6500 K

sRGB uses D65 vs ACES uses D60.

Source: https://z-fx.nl/ColorspACES.pdf

So do you understand these now?

  • LUT (Look Up Tables)
  • EOTF (Electro-Optical Transfer Function) – Linear to Non Linear or Log Conversion
  • OETF (Optio-Electro Transfer Function) – Log to Linear Conversion
  • Gamma Curve – Popular Name for EOTF
  • Gamma Correction
  • Log Curve (Non Linear Data)
  • Linear Curve (Linear Data)
  • High Dynamic Range HDR
  • Standard Dynamic Range SDR
  • White Point
  • IDT – Input Data Transform
  • ODT – Output Data Transform
  • Log LUT
  • f-Stops

A pair of Gamma and Gamut data is requied for encoding to display colors.

A device dependent RGB color space has standard primaries, gamma, and a whitepoint such as D50 or D65.

  • Primaries (R G B) for Color
  • Gamma for Luminance, and
  • White Point

Source: The Essential Guide to Color Spaces

Now that we’ve discussed these three parameters, here are some practical examples:

An Arri Alexa records media in Arri Wide Color Gamut, with an Arri Log C tone mapping curve, and a white point ranging from 2,000K to 11,000K.

A RED Dragon captures media in RedWideGamutRGB gamut, with a Log3G10 tone mapping curve, and a white point ranging from 1,700K to 10,000K (other gamut and gamma choices are available).

A cinema projector has a DCI-P3 gamut, a Gamma 2.6 tone mapping curve, and a standard illuminant D63 white point.

An SDR TV has a Rec 709 gamut, a Gamma 2.4 tone mapping curve, and a standard illuminant D65 white point.

Display Devices

  • Display Projectors
  • Television
  • Computer Monitors

Three advantages in newer display devices

  • Color
    • Color Space
    • Bit Depth
    • Gamma
    • Gamma Correction
  • Resolution
    • 4K vs 8K
  • Luminance
    • Nits

Image Source: What is 4K, UHD, SLog3, Rec 2020

Color Spaces used in Display Devices

Image Source: What is 4K, UHD, SLog3, Rec 2020

Display Resolution

Image Source: WHAT IS 4K, UHD, SLOG3, REC 2020

Bit Depth

Image Source: WHAT IS 4K, UHD, SLOG3, REC 2020

Color Specification using Color Management option in displays

Color Management in Digital Video and Cinema Production

In production of

  • Feature Film
  • Television
  • OTT
  • Live Production

SDR with REC 709 Color Space

Image Source: Understanding 4K, Ultra HD and HDR

SDR with S-Gamut3 and REC 2020

Image Source: Understanding 4K, Ultra HD and HDR

Process Flow

Image Source: Understanding 4K, Ultra HD and HDR

Live Production

Image Source: Understanding 4K, Ultra HD and HDR

Image Source: WHAT IS 4K, UHD, SLOG3, REC 2020

Operations during Production Process
  • Shoot
  • Convert
  • Edit/Grading
  • Conforming
  • Compositing/Rendering/VFX/CG
  • Convert
  • Deliverables
Color Space Hierarchy in Process Flows

  • Scene Referred – Input data has higher priority
  • Display Referred – Output data has higher priority

Source: https://z-fx.nl/ColorspACES.pdf

Source:

Process Flows in ACES

Source: https://z-fx.nl/ColorspACES.pdf

Source: https://z-fx.nl/ColorspACES.pdf

Working with ACES

Source: https://z-fx.nl/ColorspACES.pdf

CG and VFX Process Flows

Source: https://z-fx.nl/ColorspACES.pdf

The ‘Parts’ Of ACES

Source: Why Every Editor, Colorist, and VFX Artist Needs to Understand ACES

Even though ACES and its various transforms are quite mathematically complex, you can understand ACES better by understanding what each part or transform in the pipeline does.

Here’s the terminology for each of these transforms:

ACES Input Transform (aka: IDT or Input Device Transform)

The Input Transform takes the capture-referred data of a camera and transforms it into scene linear, ACES color space. Camera manufacturers are responsible for developing IDTs for their cameras but the Academy tests and verifies the IDTs. In future versions of ACES, the Academy may take on more control in the development of IDTs. IDTs, like all ACES transforms, are written using the CTL (Color Transform Language) programming language. It’s also possible to utilize different IDTs to compensate for different camera settings that might have been used.

ACES Look Transform (aka: LMT or Look Modification Transform)

The first part of what’s known as the ACES Viewing Transform (the Viewing Transform is a combination of LMT, RRT, & ODT transforms). LMTs provide a way to apply a look in a similar way to a Look Up Table (LUT). It’s important to note that the LMT happens after color grading of ACES data. Also, not every tool supports the use of LMTs.

RRT (Reference Rendering Transform)

Think of the RRT as the render engine component of ACES. The RRT converts scene referred linear data to an ultrawide display-referred data set. The RRT works in combo with the ODT to create viewable data for displays and projectors. While the Academy publishes the standard RRT, some applications have the ability to use customized RRTs (written with CTL). But many color correction systems do not provide direct access to the RRT.

ACES Output Transform (also known as the ODT or Output Device Transform)

The final step in the ACES processing pipeline is the ODT. This takes the high dynamic range data from the RRT and transforms it for different devices and color spaces. Like P3 or Rec 709, 2020, etc. Like IDTs and RRTs, ODTs are written with CTL.

Derivative Standards

Source: Why Every Editor, Colorist, and VFX Artist Needs to Understand ACES

There are also three main subsets of ACES used for finishing workflows called ACEScc, ACEScct and ACEScg:

  • ACEScc uses logarithmic color encoding and has the advantage of making color grading tools feel much more like they do when working in a log space that many colorists prefer.
  • ACEScct is just like ACEScc, but adds a ‘toe’ to the encoding. This means that lift operations respond similarly to traditional log film scans. This quasi-logarithmic behavior is described as being more milky, or foggier. ACEScct was added with the ACES 1.03 specification. It’s meant as an alternative to ACEScc based on the feedback of many colorists.
  • ACEScg utilizes linear color encoding and is designed for VFX/CGI artists so their tools behave more traditionally.

The ACES Pipeline

Source: Why Every Editor, Colorist, and VFX Artist Needs to Understand ACES

Now that we’ve defined the transforms used for ACES, understanding how the various transforms combine to form an ACES processing pipeline is pretty straightforward:

Camera Data -> Input Transform -> Color Grading -> Look Transform (optional) -> Reference Rendering Transform -> Output Transform

As mentioned, ACES is a hybrid color management system of scene referred/scene linear and display referred data.

Source: Why Every Editor, Colorist, and VFX Artist Needs to Understand ACES

Source: COLOUR MANAGEMENT BASICS

Source: COLOUR MANAGEMENT BASICS

Source: COLOUR MANAGEMENT BASICS

Source: COLOUR MANAGEMENT BASICS/Autodesk

Color Throttle

Because of bottlenecks in hardware and software, the color captured during the image/video capture process does not flow in its entirty to the displays of the users. Use of hardware and color spaces used during production process determines the output displayed. Color is thus throttled.

Color Throttle when using REC 709 Color Space

Image Source: BT.2020: How the Newest Color Range Standard Maximizes 4K Video Quality

Color Throttle when using REC 2020 Color Space

Image Source: BT.2020: How the Newest Color Range Standard Maximizes 4K Video Quality

Human Visual Dynamic Range Vs REC 2020 Range

Source: BT.2020: How the Newest Color Range Standard Maximizes 4K Video Quality

Source:

Softwares used in Post Production in Digital Video and Cinema

Source: digitalfilmpro.com

Video Editing Software and Hardware
  • Non Linear Editor
    • Avid Media Composer
    • Adobe Premiere Pro
    • Final Cut Pro
    • DaVinci Resolve – color correction plus NLE
    • Vegas Pro
  • Digital Audio Workstation
    • Avid Pro Tools
    • Apple Logic Pro X
    • Ableton Live 9
    • Cakewalk Sonar
    • Adobe Audition
  • Close-Captioning and Subtitling
    • Aegisub
    • NLEs
  • Edit Workstation
    • Edit Computer
    • Audio Equipment
    • File Sharing
      • KVM Extender
    • Editing Keyboard
    • Desk Chair
  • Digital Audio Transcipts

Creative Apps
  • RV
  • Adobe After Effects
  • Adobe Premiere Pro
  • SideFX Houdini
  • Unreal Engine
  • Unity
  • Perforce Helix Core
  • Adobe Creative Cloud
  • Adobe Illustrator
  • Autodesk 3DS Max
  • Autodesk Maya
  • Autodesk RV
  • Cinesync
  • Connect
  • Deadline
  • Foundry Hiero
  • Foundry Hiero Player
  • Foundry Nuke
  • Foundry Nuke Studio
  • Maxon Cinema 4D

Free Video Editing Tools
  • DaVinci Resolve
  • Lightworks
  • HitFilm Express
  • Avid Media Composer First
  • iMovie

Free Video Production Software Tools
  • Audacity – multitrack audio recorder
  • Ardour – DAW
  • GIMP- image editing
  • Blender – 3D Creation
  • Nuke Studio – Compositor – Node Based visual FX (VFX), editing, and finishing Studio
  • Blackmagic Fusion – Full feaured Compositor – Motion Graphics

3D Rendering Softwares
  • Unity
  • 3Ds Max Design
  • Maya
  • Cinema 4D
  • Blender
  • Keyshot
  • V-Ray
  • Lumion
  • SOLIDWORKS Visualize
  • Direct 3D
  • RenderMan
  • Redshift
  • Octane Render
  • Arnold
  • Maxwell
Color Management in Applications

Source: DISPLAY CALIBRATION & COLOR MANAGEMENT

Cameras for Video

Budget Cinema Cameras
  • Black Magic Pocket Cinema Camera
  • Black Magic Pocket Camera 4K
  • Z Cam E2C 4K Cine Camera MFT
  • Panasonic GH5

Best Cameras for Videographers

Source: Best cameras for videographers/DPREVIEW.COM

Published Nov 24, 2020

  • Panasonic Lumix DC – S1H
  • Panasonic Lumix DC-GH5
  • Canon EOS R6
  • Fujifilm X-T4
  • Nikon Z6
  • Nikon Z6 II
  • Panasonic Lumix Dc-GH5S
  • Sigma fp
  • Sony a7S III

Best 4K and 6K Cameras for Film making

Source: https://www.youtube.com/watch?v=o0muduTpveM&t=244s

  • Sony Alpha a7 III
  • Panasonic Lumix GH5S
  • Sony PXW FSM2
  • Panasonic Lumix S1H
  • Blackmagic Pocket Cinema 6K
  • Canon EOS C300 Mark II
  • Panasonic AU-EVA1
  • Blackmagic Design URSA Mini Pro G2
  • Sony PXW FS9
  • Canon C500 Mark II

Best Camcorders for Videographers

Source: Youtube

  • Panasonic HC-X2000
  • Sony PXW-Z280
  • Canon XA55
  • Panasonic AG-CX10
  • JVC GY-HC500U
  • Sony PXW-Z90
  • Panasonic HC-X1
  • Canon XF 705
  • JVC GY-HM250
  • Sony FDR -AX700

My Related Posts

Digital Color and Imaging

On Light, Vision, Appearance, Color and Imaging

Key Sources of Research

Why Every Editor, Colorist, and VFX Artist Needs to Understand ACES

Working with ACES in DaVinci Resolve

Oliver Peters

https://digitalfilms.wordpress.com/2020/10/02/working-with-aces-in-davinci-resolve/

Color Management and ACES Workflow

CG Cinematography

The Pointer’s Gamut
The coverage of real surface colors by RGB color spaces and wide gamut displays

Kid Jansen, Updated 19 February 2014

https://www.tftcentral.co.uk/articles/pointers_gamut.htm

ACES: Where Are We Now?

by Geoff Smith on August 14, 2020

https://www.abelcine.com/articles/blog-and-knowledge/tutorials-and-guides/aces-where-are-we-now

What is 4K, UHD, SLog3, Rec 2020

And other really boring things.

Compiled By Peter Morrone

BT.2020: How the Newest Color Range Standard Maximizes 4K Video Quality

BenQ

2020/05/29

https://www.benq.com/en-us/knowledge-center/knowledge/bt2020.html

Color Spaces in Visual Effects

Color Spaces

February 15, 2019

https://ciechanow.ski/color-spaces/

Chapter 1 Color Management

Color Spaces / MAYA/Autodesk

https://knowledge.autodesk.com/support/maya/learn-explore/caas/CloudHelp/cloudhelp/2020/ENU/Maya-Rendering/files/GUID-4410C27C-BB49-491B-AD13-14F48A8CCAAE-htm.html

Elle Stone’s Well-Behaved ICC Profiles and Code

https://ninedegreesbelow.com/photography/lcms-make-icc-profiles.html

ACES Workflow

Common Color Spaces

Color for Motion Pictures and Games

From Design to Display
  • Haarm-Pieter Duiker
  • Alex Forsythe
  • Stefan Luka
  • Thomas Mansencal
  • Jeremy Selan
  • Kevin Shaw
  • Nick Shaw

A VES Technology Committee White Paper
2019

https://nick-shaw.github.io/cinematiccolor/common-rgb-color-spaces.html

Cinematic Color From Your Monitor to the Big Screen

A VES Technology Committee White Paper Oct 17, 2012

Color Enhancement and Rendering in Film and Game Production: Color Management

Joseph Goldstone Lilliputian Pictures LLC

COLOR CORRECTION HANDBOOK:
Professional Techniques for Video and Cinema

Second Edition 

Alexis Van Hurkman

Peachpit Press http://www.peachpit.com

Colour Appearance Issues in Digital Video, HD/UHD, and D‐cinema

Charles Poynton

Understanding Color Management,

Second Edition

First published:18 July 2018

https://onlinelibrary.wiley.com/doi/book/10.1002/9781119223702

COLOR MANAGEMENT WITH CINEMA

Red

https://www.red.com/red-101/cinema-color-management

Digital Color Management

Encoding Solutions

Giorgianni, Edward J / Madden, Thomas E

The Basics of High Dynamic Range Media Explained [u]

Posted on July 27, 2019 by Larry

Understanding 4K, Ultra HD and HDR

Sony

COLOUR REPRODUCTION IN ELECTRONIC IMAGING SYSTEMS

PHOTOGRAPHY, TELEVISION, CINEMATOGRAPHY

Michael S Tooms

Digital Camera Reviews and Sensor Performance Summary

by Roger N. Clark

https://clarkvision.com/imagedetail/digital.sensor.performance.summary/

How to Use Dynamic Range for Stunning Photos in Bright Light

2 CCD , 3 CCD cameras, 4 CCD and 3 CMOS Cameras

http://www.adept.net.au/cameras/2CCD_3CCD_Cameras.shtml

CCD Sensors, Albert Einstein, and the Photoelectric Effect

https://www.radiantvisionsystems.com/blog/ccd-sensors-albert-einstein-and-photoelectric-effect

Color Management for Photographers – A Simplified Guide

Camera Sensor Sizes Explained: What You Need to Know

https://www.studiobinder.com/blog/camera-sensor-size/

Reading 15: Color

http://web.mit.edu/6.813/www/sp18/classes/15-color/

The Fundamentals of Camera and Image Sensor Technology

Jon Chouinard

Understanding color & the in-camera image processing pipeline for computer vision

Dr. Michael S. Brown

Digital Image Sensors

https://www.sensorland.com/HowPage090.html

Color Spaces, Log and Gamma

3.4 Color Spaces, Log and Gamma

LOG COLOR IN-DEPTH

Renderstory

Exploring the Basic Concepts of HDR: Dynamic Range, Gamma Curves, and Wide Color Gamut

Abhay Sharma

https://onlinelibrary.wiley.com/doi/pdf/10.1002/msid.1060

Understanding RGB Color Spaces for Monitors, Projectors, and Televisions

Abhay Sharma

First published: 26 March 2019

https://onlinelibrary.wiley.com/doi/full/10.1002/msid.1020

UHDTV – HDR and WCG

Understanding UHDTV Displays with PQ/HLG HDR, and WCG

https://www.lightspace.lightillusion.com/uhdtv.html

Color Management

https://docs.blender.org/manual/en/latest/render/color_management.html

Color Space Management: sRGB, Linear and Log

https://tiberius-viris.artstation.com/blog/3ZBO/color-space-management-srgb-linear-and-log

GAMMA AND LINEAR SPACE – WHAT THEY ARE AND HOW THEY DIFFER

https://www.kinematicsoup.com/news/2016/6/15/gamma-and-linear-space-what-they-are-how-they-differ

Are S-Log and Color Space separate things?

Understanding Log and Color Space In Compositing

RENDER COLOR SPACES

23 JUNE 2016

Anders Langlands

https://www.colour-science.org/anders-langlands/

Understanding High Dynamic Range (HDR) Imaging by Curtis Clark, ASC 

A Cinematographer Perspective

https://cms-assets.theasc.com/curtis-clark-asc-understanding-high-dynamic-range.pdf?mtime=20180502122857

Color Science Fundamentals in Motion Imaging

March 14, 2019 01:00 PM

https://www.smpte.org/events/color-science-fundamentals-in-motion-imaging

What is RAW Development?

Colour Management Basics

Autodesk Feb 2020

The Best Rendering Software for CG Lighting for Animation

by Tina Lee | Feb 14, 2019

C. A. Bouman: Digital Image Processing

January 7, 2020

The Essential Guide to Color Spaces

Cullen Kelly

Dell Color Management Software

User Manual

Adjusting for the Scene Adopted White

White Point Conversion

https://knowledge.autodesk.com/support/maya/learn-explore/caas/CloudHelp/cloudhelp/2016/ENU/Maya/files/GUID-2C925F6A-5A9C-4B2B-B732-90F4C3D2EB49-htm.html

A Complex Color Management Example

https://knowledge.autodesk.com/support/maya/learn-explore/caas/CloudHelp/cloudhelp/2016/ENU/Maya/files/GUID-7D579180-1E60-43DD-BB9C-0C00D1968F53-htm.html

Common Color Management Scenarios

https://knowledge.autodesk.com/support/maya/learn-explore/caas/CloudHelp/cloudhelp/2016/ENU/Maya/files/GUID-B2CD60E0-C100-45A4-9595-84D2DF98B268-htm.html

A Conversation about White Point and Digital Displays [Interview]

https://www.nanolumens.com/blog/an-imaginary-conversation-about-white-point-and-digital-displays/

Gamma and White Point Explained: How to Calibrate Your Monitor

https://blogs.scientificamerican.com/symbiartic/how-to-calibrate-your-monitor/

Why is the media white point of a display profile always D50?

http://www.color.org/whyd50.xalter

Colour Management for Video Editors

Display Calibration & Color Management

https://www.mysterybox.us/blog/2017/9/7/display-calibration-color-management

Color Communication

How does a digital camera sensor work?

On Light, Vision, Appearance, Color and Imaging

On Light, Vision, Appearance, Color and Imaging

This is a topic close to my heart. My masters thesis research was on color prediction and modeling. My research work was published by IPST Atlanta as Technical paper no 469. Those who work in Paper and Printing Industry know IPST very well. It used to be called Institute of Paper Chemistry and was based in Appleton, Wisconsin.

Key Terms

  • Color Science
  • Human Vision
  • Color Models
  • Industrial Color
  • Measurement
  • Color Physics
  • Color Chemistry
  • Color Perception
  • Color Psychology
  • Instruments
  • Light
  • Color Technology
  • Light Absorption
  • Light Scattering
  • Psycho-Physics of Color
  • Reflectance
  • Refraction
  • Gloss
  • Texture
  • Colorimeter
  • Spectrophotometer
  • Color Dyes and Pigments
  • Paint, Plastics, Paper, Textiles
  • Digital Color
  • Device Independent color
  • Computer Monitors
  • Color Theory
  • Color Physics
  • Kubelka Munk Theory
  • Munsell Colors
  • Pantone Colors
  • RIT
  • Newton’s Optics
  • Goethe Color Theory
  • Four Color Problem
  • Primary Colors
  • CIE LAB color
  • CIE LCH color
  • Visual Match
  • Instrument Match
  • Radiative Transfer Theory
  • Two Flux vs Multi Flux Models
  • CIE
  • ICC
  • Optical Society of America
  • Inter-Society Color Council ISCC
  • Color and Appearance
  • Whiteness
  • Yellowness
  • Color Profiles
  • Color Scales
  • CIE XYZ
  • RGB
  • CMYK
  • Rods and Cones

Human Vision

Retina of Human eye has two kind of cells responsible for color vision

Rod Cells. Rod Cells are used for motion and lightness

Cone Cells. Cone Cells are responsible for color vision in the eye retina.

Image Source: Basics of Color Imaging/Yao Wang

Image Source: Basics of Color Imaging/Yao Wang

Image Source: Clarkvision

In the references, I have included many links to articles and papers on the following importatnt topics of color. Many companies who meaure and do testing of color provide excellent tutorials on color. See References.

  • Light and Visible Spectrum
  • What is Color?
  • Color Perception in Human
  • Color Models for Visual Perception
  • Color Physics
  • Dyes and Pigments
  • Color Chemistry
  • Optical Properties of Materials

Color Standards

  • ICC International Color Consortium
  • CIE
  • ISCC Inter Society Color Council

Coloring of Materials

  • Paper
  • Textiles
  • Paints
  • Plastics

Color Meaurement in Industry

  • Colorimeters
  • Spectrophotometers

Color Measurement Companies

  • Xrite
  • Datacolor
  • Konica Minolta
  • Hunterlab
  • Technidyne

Color Prediction and Control

  • Prediction in Lab
  • Online Prediction and Control

Kubelka Munk Theory (KM)

It was developed using Radiative Transfer Theory to measure Light Absorption and Light Scattering by objects. Reflection and Transmission.

Limitations of KM Theory

  • Only Two Flux
  • Errors in measuring Strong Absorption and Weak Scattering
  • Correlation between K and S. As K goes up S goes down
  • Use of Single Constant Vs Two Constant KM Theory
  • Can not measure effects of Fluroscent Dyes FWA OBA

Several efforts have been made since early 1990s, to revise, modify KM theory or develop other multiflux models to improve prediction better than KM model.

Key Recent Researchers

  • Li Yang
  • Per Edstrom
  • L G Coppel
  • Tarja Shakespeare
  • H Granberg

My related posts

Some of my earlier published papers

Sounds True: Speech, Language, and Communication

Myth of Invariance: Sound, Music, and Recurrent Events and Structures

Understanding Rasa: Yoga of Nine Emotions

Key sources of Research

Measurement and Control of the Optical Properties of Paper

Technidyne

https://www.technidyne.com/product-page/measurement-and-control-of-the-optical-properties-of-paper

https://imisrise.tappi.org/TAPPI/Products/20/MCOPP/20MCOPP.aspx

Optical paper properties and their influence on colour reproduction and perceived print quality

Authors:

Ivana Jurič

Igor Karlovits

Ivana Tomić

Dragoljub Novaković

https://www.researchgate.net/publication/275637561_Optical_paper_properties_and_their_influence_on_colour_reproduction_and_perceived_print_quality

An assessment of Saunderson corrections to the diffuse reflectance of paint films

A García-Valenzuela et al 

2011 J. Phys.: Conf. Ser. 274 012125

https://iopscience.iop.org/article/10.1088/1742-6596/274/1/012125/pdf

Review: Optical properties of paper: theory and practice.

R. Farnood.

In Advances in Pulp and Paper Research, Oxford 2009, 

Trans. of the XIVth Fund. Res. Symp. Oxford, 2009,
(S.J. I’Anson, ed.), pp 273–352, FRC, Manchester, 2018

Diffuse Reflectance Spectroscopy; Applications, Standards, and Calibration (With Special Reference to Chromatography)

R. W. Frei

Analytical Research and Development, Pharmaceutical Department Sandoz Ltd., 4002 Basel, Switzerland

(May 26, 1976)

Optical models for colored materials

Mathieu Hébert
Institut d’Optique Graduate School, Saint-Etienne. mathieu.hebert@institutoptique.fr

The Use of Reflectance Measurements in the Determination of Fixation of Reactive Dyes to Cotton

N. Ahmed, D. P. Oulton, J. A. Taylor*

Textile sand Paper Group, School of Materials, University of Manchester, P.O. Box 88, Sackville Street, Manchester M60 1QD, United Kingdom

Received 3 January 2005; accepted 9 August 2005

Two-flux and multiflux matrix models for colored surfaces

Mathieu Hébert

Université de Lyon, Université Jean Monnet de Saint-Etienne, CNRS UMR 5516 Laboratoire Hubert Curien, F-42000, Saint-Etienne, France.

Patrick Emmel
14 rue de Münchendorf, 68220 Folgensbourg, France.

https://hal.archives-ouvertes.fr/hal-01179591/document

DETERMINING SCATTERING AND ABSORPTION COEFFICIENTS BY DIFFUSE ILLUMINATION

USDA 1967

F. A. SIMMONDS and C. L. COENS

Optical Response from Paper

Doctoral Thesis

H Granberg 2003

Sweden

PAPER’S APPEARANCE: A REVIEW

Martin A. Hubbe, Joel J. Pawlak and Alexander A. Koukoulas

2008 BioResources online Journal

Examination of the revised Kubelka–Munk theory: considerations of modeling strategies

Per Edström

Department of Engineering, Physics and Mathematics, Mid Sweden University, SE-87188 Härnösand, Sweden

Received April 5, 2006; revised July 3, 2006; accepted July 18, 2006; posted September 11, 2006 (Doc. ID 70185); published January 10, 2007

Revised KubelkaMunk theory. I. Theory and application

Li Yang and Bjo ̈rn Kruse

Campus Norrko ̈ ping (ITN), Linko ̈ ping University, S-601 74, Norrko ̈ ping, Sweden

Received November 20, 2003; revised manuscript received May 3, 2004; accepted May 5, 2004

Revised Kubelka–Munk theory II Unified framework for homogeneous and inhomogeneous optical media

Article in Journal of the Optical Society of America A · November 2004

Li Yang, Bjo ̈rn Kruse, and Stanley J. Miklavcic

Campus Norrko ̈ ping (ITN), Linko ̈ ping University, S-601 74, Norrko ̈ ping, Sweden

Revised Kubelka–Munk theory. III. A general theory of light propagation in scattering and absorptive media

Li Yang

Graphical Technology/Package Printing Group, Department of Chemical Engineering, Karlstad University, S-651 88 Karlstad, Sweden

Stanley J. Miklavcic

Center for Creative Media Technology, Department of Science and Technology, Linköping University, S-601 74 Norrköping, Sweden

Received January 18, 2005; accepted March 9, 2005

Qualifying the arguments used in the derivation of the revised Kubelka-Munk theory: reply

Yang, Li 

Linköping University, The Institute of Technology. Linköping University, Department of Science and Technology.2007 (English)

In: JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, ISSN 1084-7529, Vol. 24, no 2, p. 557-560

A novel method for studying ink penetration of a print.

Yang L, Fogden A, Pauler N, Sävborg Ö, Kruse B.

Nordic Pulp & Paper Research Journal. 2005;20(4):423-429.

INK-PAPER INTERACTION

A study in ink-jet color reproduction

L i Y a n g 2003

Department of Science and Technology Link ̈oping University

SE-601 74 Norrko ̈ping Sweden

Color Prediction and Separation Models in Printing

-Minimizing the Colorimetric and Spectral Differences employing Multiple Characterization Curves

Yuanyuan Qu

Department of Science and Technology Linköping University, SE-601 74 Norrköping, Sweden Norrköping 2013

Deriving Kubelka–Munk theory from radiative transport 

Christopher Sandoval and Arnold D. Kim*

Applied Mathematics Unit, School of Natural Sciences, University of California, Merced, 5200 North Lake Road, Merced, California 95343, USA
*Corresponding author: adkim@ucmerced.edu

Received November 12, 2013; accepted January 6, 2014;
posted January 16, 2014 (Doc. ID 201164); published February 21, 2014

KUBELKA-MUNK THEORY IN DESCRIBING OPTICAL PROPERTIES OF PAPER (I)

Vesna Džimbeg-Malčić, Željka Barbarić-Mikočević, Katarina Itrić

KUBELKA-MUNK THEORY IN DESCRIBING OPTICAL PROPERTIES OF PAPER (II).

  • Source: Tehnicki vjesnik / Technical Gazette . Jan-Mar2012, Vol. 19 Issue 1, p191-196. 6p. 
  • Author(s): Džimbeg-Malčić, Vesna; Barbarić-Mikočević, Željka; Itrić, Katarina

Applicability conditions of the Kubelka–Munk theory

William E. Vargas and Gunnar A. Niklasson

Extension of the Kubelka–Munk theory of light propagation in intensely scattering materials to fluorescent media 

Leonid Fukshansky and Nina Kazarinova

  • Journal of the Optical Society of America
  • Vol. 70,
  • Issue 9,
  • pp. 1101-1111
  • (1980)

What Has Been Overlooked in Kubelka-Munk Theory?

Author: Yang, Li

Source: NIP & Digital Fabrication Conference, 2005 International Conference on Digital Printing Technologies. Pages 332-679., pp. 376-379(4)

Publisher: Society for Imaging Science and Technology

https://www.ingentaconnect.com/content/ist/nipdf/2005/00002005/00000002/art00012?crawler=true

Kubelka Munk Theory for Efficient Spectral Printer Modeling

Mekides Assefa

https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/143732/FinalThesisReportMekidesAssefaHIG2.pdf?sequence=1

On Measurements of Effective Residual Ink Concentration (ERIC) of Deinked Papers Using Kubelka-Munk Theory

D.W. Vahey, J.Y. Zhu and C.J. Houtman

Single‐constant simplification of Kubelka‐Munk turbid‐media theory for paint systems—A review

Roy S. Berns Mahnaz Mohammadi

First published: 25 April 2007

Color Research and Application J

https://onlinelibrary.wiley.com/doi/abs/10.1002/col.20309

Spectrophotometric color prediction of mineral pigments with relatively large particle size by single- and two-constant Kubelka-Munk theory

Authors: Li, JunfengWan, Xiaoxia

Source: Color and Imaging Conference, Volume 2017, Number 25, September 2017, pp. 324-329(6)

Publisher: Society for Imaging Science and Technology

https://www.ingentaconnect.com/content/ist/cic/2017/00002017/00000025/art00054

Theory of light propagation incorporating scattering and absorption in turbid media

Li Yang and Stanley J. Miklavcic

Department of Science and Technology, Link ̈oping University, S-601 74, Norrko ̈ping, Sweden

Article in Optics Letters · May 2005

Kubelka-Munk Model for Imperfectly Diffuse Light Distribution in Paper

Li Yang􏰀
Holmen Paper Development Center (HPD), Holmen AB, Sweden E-mail: li.yang@holmenpaper.com

R. D. Hersch

Ecole Polytechnique Fédérale de Lausanne (EPFL), School of Computer and Communication Sciences, Lausanne 1015, Switzerland

Quantification of the Intrinsic Error of the Kubelka–Munk Model Caused by Strong Light Absorption

H. GRANBERG and P. EDSTRÖM

JOURNAL OF PULP AND PAPER SCIENCE: VOL. 29 NO. 11 NOVEMBER 2003

Anisotropic reflectance from turbid media. I. Theory

Neuman, Magnus 

Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.(Pappersoptik och färg)

Edström, Per 

Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.(Pappersoptik och färg)

2010 (English)

In: Journal of the Optical Society of America A, ISSN 0740-3232, Vol. 27, no 5, p. 1032-1039

Mathematical modeling and numerical tools for simulation and design of light scattering in paper and print

Edström, Per 

Mid Sweden University, Faculty of Science, Technology and Media, Department of Engineering, Physics and Mathematics.(FSCN – Fibre Science and Communication Network)ORCID iD: 0000-0002-0529-1009

Mid Sweden University

2007 (English)

Theoretical Investigation of Bioactive Papers Using the Kubelka-Munk Theory

Elina Levi Gendler

Masters of Applied Science Chemical Engineering and Applied Chemistry University of Toronto
2015

The color prediction model of fluorescent prints

Na DongYixin ZhangGuoyun Shi

Proceedings Volume 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications;72411N (2009) 
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7241/72411N/The-color-prediction-model-of-fluorescent-prints/10.1117/12.808459.short?SSO=1

State of the art on macroscopic models for the determination of thin films optical properties

G. Saridakis, D. Kolokotsa

Technological Educational Institute of Crete, Greece

M. Santamouris

Radiative properties of optically thick fluorescent turbid media

Alexander A. Kokhanovsky

Journal of the Optical Society of America AVol. 26,Issue 8,pp. 1896-1900(2009)

https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-26-8-1896

Radiative properties of optically thick fluorescent turbid media: errata 

A. A. Kokhanovsky  

  • Journal of the Optical Society of America
  • Vol. 27,
  • Issue 9,
  • pp. 2084-2084
  • (2010)

https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-27-9-2084

Spectral Reflectance Model of a Single Sheet of Blank Paper*

Yongchi XU** and Shisheng ZHOU** **

Faculty of Printing and Packaging Engineering, Xi’an University of Technology, Xi’an, 710048 China

https://www.jstage.jst.go.jp/article/nig/51/2/51_103/_pdf

Next Generation Simulation Tools for Optical Properties in Paper and Print

Per Edström
Mid Sweden University, TFM, SE‐87188 Härnösand, Sweden,

Improving the performance of computer color matching procedures 

  • Journal of the Optical Society of America A
  • Vol. 25,
  • Issue 9,
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https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-25-9-2251

A two-phase parameter estimation method for radiative transfer problems in paper industry applications

Per Edstro ̈ m*

Department of Engineering, Physics and Mathematics, Mid Sweden University, Ha ̈rno ̈sand, Sweden

Inverse Problems in Science and Engineering

Vol. 16, No. 7, October 2008, 927–951

A Guide to Understanding Color

Xrite

Understanding CIE *L*a*b Colour Space

Kydex

Understanding Color

Giordino Beretta 2008 and 2010

HP Labs

SPIE

PRECISE COLOR COMMUNICATION  : COLOR CONTROL FROM PERCEPTION TO INSTRUMENTATION

Konica Minolta

The basics of Color Perception and Measurement

HunterLab

The Color Guide and Glossary

Xrite

Color Differences & Tolerances Commercial Color Acceptability

Datacolor

Defining and Communicating Color: The CIELAB System

SAPPI

Color Science Course

Berns

RIT

ftp://ftp.cis.rit.edu/mcsl/berns/Berns_color_course.pdf

Using Color Effectively in Computer Graphics

Lindsay W. MacDonald

University of Derby, UK

Color Management Fundamentals

Color realism and color science

Alex Byrne

Department of Linguistics and Philosophy, Massachusetts Institute of Technology, Cambridge, MA 02139
abyrne@mit.edu mit.edu/abyrne/www

David R. Hilbert

Department of Philosophy and Laboratory of Integrative Neuroscience, University of Illinois at Chicago, Chicago, IL 60607
hilbert@uic.edu http://www.uic.edu/~hilbert/

BEHAVIORAL AND BRAIN SCIENCES (2003) 26, 3–64 

Introduction to Color Models

Routledge

Color Appearance Models

Second Edition

Mark D. Fairchild

Munsell Color Science Laboratory Rochester Institute of Technology, USA

COLOR IN GEMS: THE NEW TECHNOLOGIES

By George R. Rossman

THE NATURE OF LIGHT AND COLOR

Kodak

Light and Color

Colour physics and colour measurement: state-of-the-art and challenges

S Westland

THE PHYSICS OF COLOUR

Mil􏰀osz Michalski

Institute of Physics Nicolaus Copernicus University

July 3, 2012

Lecture 26: Color and Light

On the Kubelka-Munk Single-Constant/Two-Constant Theories

Ning Pan and others

https://www.researchgate.net/publication/216567998_On_the_Kubelka-Munk_Single-ConstantTwo-Constant_Theories

Kubelka-Munk Prediction for Dark Mixtures

  • December 2013
  • Conference: 5th International Color and Coatings Congress (ICCC 2013)
  • At: Isfahan, Iran

Authors:

Farhad Moghareh Abed

Roy S. Berns

https://www.researchgate.net/publication/323656636_Kubelka-Munk_Prediction_for_Dark_Mixtures

Colour Measurement and Analysis in Fresh and Processed Foods: A Review

Pankaj B Pathare

Umezuruike Linus Opara

Fahad Al-Julanda Al-Said

https://www.researchgate.net/publication/225037588_Colour_Measurement_and_Analysis_in_Fresh_and_Processed_Foods_A_Review

Extending Kubelka-Munk’s Theory with Lateral Light Scattering

Safer Mourad *, Patrick Emmel **, Klaus Simon and Roger David Hersch **

IS&T’s NIP17: International Conference on Digital Printing Technologies

Kubelka Munk Model in Paper Optics: Successes, Limitations and Improvements

L. Yang

Page 81

DETERMINATION OF OPTICAL CHARACTERISTICS OF MATERIALS FOR COMPUTER COLORANT ANALYSIS

Gülen Bayhan

https://www.academia.edu/5407157/DETERMINATION_OF_OPTICAL_CHARACTERISTICS_OF_MATERIALS_FOR_COMPUTER_COLORANT_ANALYSIS

DETERMINATION OF OPTICAL CHARACTERISTICS OF MATERIALS FOR COMPUTER COLORANT ANALYSIS

Dibakar Raj Pant.

University of Joensuu Department of Computer Science Pro gradu
April, 2006

ftp://www.cs.joensuu.fi/pub/Theses/2005_MSc_Pant_Dibakar_Raj.pdf

Next Generation Simulation Tools for Optical Properties in Paper and Print

Per Edström
Mid Sweden University, TFM, SE‐87188 Härnösand, Sweden, per.edstrom@miun.se

The optical properties of bleached kraft pulp

Steven R. Middleton and Anthony M. Scallan, 

Pulp and Paper Research Institute of Canada, Pointe Claire, Canada

Light Scattering in Fibrous Sheets

Edwin W Arnold

IPC PhD Thesis 1962

https://smartech.gatech.edu/bitstream/handle/1853/5809/arnold_ew.pdf?…

INFLUENCE OF LIGHT AND TEMPERATURE ON OPTICAL PROPERTIES OF PAPERS

BARBARA BLAZNIK, DIANA GREGOR-SVETEC and SABINA BRAČKO

Department of Information and Graphic Arts Technology, Faculty of Natural Sciences and Engineering, University of Ljubljana, Snežniška 5, SI-1000 Ljubljana, Slovenia

Determining optical properties of mechanical pulps 

Anette Karlsson, Sofia Enberg, Mats Rundlöf, Magnus Paulsson and Per Edström

Nordic Pulp and Paper Research Journal Vol 27 no.3/2012

Color iQC and Color iMatch Multi Flux Matching Guide

Version 8.0 | July 2012

Xrite

Industrial Color Physics 

By Georg A. Klein

PREDICTION OF PAPER COLOR:
A PROCESS SIMULATION APPROACH

G.L. JONES, M. CHATURVEDI, AND R. ARAVAMUTHAN

MARCH 1993

IPST Technical Paper Series 469

Click to access tps-469.pdf

Application of Kubelka-Munk Theory in Device-independent Color Space Error Diffusion

Shilin Guo and Guo Li

Hewlett-Packard Company, San Diego Site

The Practical Guide To Color Theory For Photographers

In-Depth Guide on How to Measure Color in Plastics

https://www.ptonline.com/articles/in-depth-guide-on-how-to-measure-color-in-plastics

A Guide to Understanding Color Communication

Tintometer Group

A partial explanation of the dependence between light scattering and light absorption in the Kubelka-Munk model 

M. Neuman, L. G. Coppel and P. Edström

Nordic Pulp and Paper Research Journal Vol 27 no.2/2012

Limitations of the efficiency of fluorescent whitening agents in uncoated paper

Gustafsson Coppel, Ludovic 

Andersson, Mattias 

Edström, Per 

Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.

Kinnunen, Jussi 

Univ Eastern Finland, Dept Math & Phys, FI-80101 Joensuu, Finland.

2011 (English) In: Nordic Pulp & Paper Research Journal, ISSN 0283-2631, E-ISSN 2000-0669, Vol. 26, no 3, p. 319-328

Determination of light scattering coefficient of dark and heavy sheets

KNOX, J.M., and WAHREN, D.

Tappi J 1984

Whiteness and Fluorescence in Layered Paper and Boards

Perception and Optical Modelling

L G Coppel

PhD Thesis

Mid Sweden University

Extension of the Stokes equation for layered constructions to fluorescent turbid media

Ludovic G. Coppel,1,2 Magnus Neuman,2 and Per Edström2,*
1Innventia AB, Box 5604, SE-11486 Stockholm, Sweden
2Department of Natural Sciences, Engineering and Mathematics, Mid Sweden University, SE-87188 Härnösand, Sweden 

*Corresponding author: per.edstrom@miun.se

Received January 3, 2012; accepted January 20, 2012;
posted January 24, 2012 (Doc. ID 160521); published March 22, 2012

Determination of quantum efficiency in fluorescing turbid media.

Coppel LG,  Andersson M,  Edström P

Applied Optics, 31 May 2011, 50(17):2784-2792

Extension of the Kubelka–Munk theory of light propagation in intensely scattering materials to fluorescent media 

Leonid Fukshansky and Nina Kazarinova

  • Journal of the Optical Society of America
  • Vol. 70,
  • Issue 9,
  • pp. 1101-1111
  • (1980)

https://www.osapublishing.org/josa/abstract.cfm?uri=josa-70-9-1101

Revised Optical Properties of Turbid Media on a Base of Generally Improved Two-Flux Kubelka-Munk Approach

D. A. Rogatkin1, and V. V. Tchernyi2

Understanding Color Communication

Xrite

Correspondences between the Kubelka-Munk and the Stokes model of strongly light-scattering materials. II: Implications

OLF, H. G
[1] North Carolina state univ., dep. wood & paper sci., Raleigh NC 27695-8005, United StatesSource

Tappi journal1989, Vol 72, Num 7, pp 159-163

Precise Color Communication

Konica Minolta

The Color Guide and Glossary

Xrite

CIE LAB Color

Sappi

Principles of Color Technology for Color Imaging Scientists and Engineers

Berns

RIT

ftp://ftp.cis.rit.edu/mcsl/berns/Berns_color_course.pdf

Using Color Effectively in Computer Graphics

Lindsay W. MacDonald

University of Derby, UK

Color Management Fundamentals Wide Format Series

Introduction to Color Models

Anisotropic reflectance from turbid media. I. Theory

Neuman, Magnus 

Edström, Per 

Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.(Pappersoptik och färg)

2010 (English)In: Journal of the Optical Society of America A, ISSN 0740-3232, Vol. 27, no 5, p. 1032-1039

Anisotropic reflectance from turbid media. II. Measurements 

Magnus Neuman and Per Edström

  • Journal of the Optical Society of America A
  • Vol. 27,
  • Issue 5,
  • pp. 1040-1045
  • (2010)

https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-27-5-1040

Angular dependence of fluorescence from turbid media

Ludovic G. Coppel,1,∗ Niklas Johansson,and Magnus Neuman2

https://www.researchgate.net/publication/281069011_Angular_dependence_of_fluorescence_from_turbid_media

Limitations in the efficiency of fluorescent whitening agents in uncoated paper

Ludovic G. Coppel, Mattias Andersson, Per Edström and Jussi Kinnunen

Fluorescence model for multi-layer papers using conventional spectrophotometers

 L. G. Coppel, M. Andersson, M. Neuman and P. Edström

Nordic Pulp & Paper Research Journal | Volume 27: Issue 2

Whiteness Assessment: A Primer Concepts, Determination and Control of Perceived Whiteness

September 2006

Claudio Puebla

https://www.researchgate.net/publication/331802584_Whiteness_Assessment_A_Primer_Concepts_Determination_and_Control_of_Perceived_Whiteness

FLUORESCENCE AND THE PAPER APPEARANCE – CHALLENGES IN PAPER COLORING

Dr. Tarja Shakespeare1, Dr. John Shakespeare2

2009

MODELING A COLORING PROCESS 

Tarja Shakespeare, John Shakespeare 

US Patent

A fluorescent extension to the Kubelka–Munk model

Tarja Shakespeare

John Shakespeare

https://www.researchgate.net/publication/229559432_A_fluorescent_extension_to_the_Kubelka-Munk_model

Radiative properties of optically thick fluorescent turbid media

Alexander A Kokhanovsky 1

https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-26-8-1896

A New Look at Fundamentals of the Photometric Light Transport and Scattering Theory. Part 2: One-Dimensional Scattering with Absorption

Authors: Persheyev S.Rogatkin D.A.Published: 22.11.2017 
Published in issue: #6(75)/2017 
DOI: 10.18698/1812-3368-2017-6-65-78

http://vestniken.ru/eng/catalog/phys/opt/787.html

Spectral prediction model for color prints on paper with fluorescent additives.

Hersch RD1

Applied Optics, 30 Nov 2008, 47(36):6710-6722

https://europepmc.org/article/med/19104523

Relationship between the Kubelka-Munk scattering and radiative transfer coefficients

Suresh N Thennadil 1

https://pubmed.ncbi.nlm.nih.gov/18594602/

Effect of strong absorption on the Kubelka-Munk scattering coefficient

A. KoukoulasB. Jordan

Published 1997

https://www.semanticscholar.org/paper/Effect-of-strong-absorption-on-the-Kubelka-Munk-Koukoulas-Jordan/fee09ae8d3bfd2e8d58eff34321f60eec89d445b

A note concerning the interaction between light scattering and light absorption in the application of the Kubelka-Munk equations

Mats RundlöfJ. A. Bristow

Published 1997

https://www.semanticscholar.org/paper/A-note-concerning-the-interaction-between-light-and-Rundlöf-Bristow/c87c601ad12a90ba9e241469dd45f85797c19f70

Color Measurements on Prints Containing Fluorescent Whitening Agents

Mattias Andersson and Ole Norberg

Digital Printing Center, Mid Sweden University, 89118 Örnsköldsvik, Sweden

https://www.researchgate.net/publication/238022968_Color_measurements_on_prints_containing_fluorescent_whitening_agents_-_art_no_64930Q

Colorant modelling for on-line paper coloring: evaluations of models and an extension to Kubelka-Munk model

Shakespeare, T. (2000)

Tampere University of Technology

https://www.researchgate.net/publication/328873794_Colorant_Modelling_for_On-Line_Paper_Coloring_Evaluations_of_Models_and_an_Extentsion_to_Kubelka-Munk_Model

Fluorescent White Dyes: Calculation of Fluorescence from Reflectivity Values 

Eugene Allen

1964 OSAJ

https://www.osapublishing.org/josa/abstract.cfm?uri=josa-54-4-506

Extension of the Kubelka–Munk theory for fluorescent turbid media to a nonopaque layer on a background

Article in Journal of the Optical Society of America A · July 2011

https://www.researchgate.net/publication/51472634_Extension_of_the_Kubelka-Munk_theory_for_fluorescent_turbid_media_to_a_nonopaque_layer_on_a_background

Tutorial on Fluorescence and Fluorescent Instrumentation

Colour measurement in practice 

Contemporary wool dyeing and finishing

Dr Rex Brady Deakin University

Separation of the Spectral Radiance Factor Curve of Fluorescent Substances into Reflected and Fluoresced Components 

Eugene Allen

  • Applied Optics
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https://www.osapublishing.org/ao/abstract.cfm?uri=ao-12-2-289

Fluorescence and kubelka‐munk theory

James S. Bonham

First published: Autumn (Fall) 1986

Color Research and Application J

https://onlinelibrary.wiley.com/doi/abs/10.1002/col.5080110310

Spectrophotometry of fluorescent pigments

R Donaldson1

1954


British Journal of Applied PhysicsVolume 5Number 6

https://iopscience.iop.org/article/10.1088/0508-3443/5/6/303

KUBELKA-MUNK THEORY OF FLUORESCENT COLORANTS

He Guoxin (Department of Textile Technology)

1988

http://en.cnki.com.cn/Article_en/CJFDTotal-DHDZ198804018.htm

Problems in colour measurement of fluorescent paper grades

Tarja Shakespeare John Shakespeare11

Analytica Chimica Acta

Volume 380, Issues 2–3, 2 February 1999, Pages 227-242

https://www.sciencedirect.com/science/article/abs/pii/S0003267098004838

Spectral Colour Prediction Model for a Transparent Fluorescent Ink on Paper*

Patrick Emmel, Roger David Hersch

Laboratoire de Systèmes Périphériques

Ecole Polytechnique Fédérale de Lausanne (EPFL),

The extended Kubelka–Munk theory and its application to spectroscopy

2020

https://link.springer.com/article/10.1007/s40828-019-0097-0

The color prediction model of fluorescent prints

Na DongYixin ZhangGuoyun Shi

Author Affiliations +Proceedings Volume 7241, Color Imaging XIV: Displaying, Processing, Hardcopy, and Applications;72411N (2009) 
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7241/72411N/The-color-prediction-model-of-fluorescent-prints/10.1117/12.808459.short?SSO=1

REVIEW: USE OF OPTICAL BRIGHTENING AGENTS (OBAs) IN THE PRODUCTION OF PAPER CONTAINING HIGH-YIELD PULPS

He Shi,a Hongbin Liu,a,b,* Yonghao Ni,a,c Zhirun Yuan,d Xuejun Zou,d and Yajun Zhou

The Kubelka-Munk Theory for Color Image Invariant Properties

Jan-Mark Geusebroek, Theo Gevers, Arnold W.M. Smeulders Intelligent Sensory Information Systems, University of Amsterdam

Kruislaan 403, 1098 SJ Amsterdam, The Netherlands

Determination of quantum efficiency in fluorescing turbid media 

Ludovic Gustafsson Coppel, Mattias Andersson, and Per Edström

Applied OpticsVol. 50,Issue 17,pp. 2784-2792(2011)

https://www.osapublishing.org/ao/abstract.cfm?uri=ao-50-17-2784

4.2 Colour Science

ALAN MARTIN

Quantification of the Intrinsic Error of the Kubelka–Munk Model Caused by Strong Light Absorption

H. GRANBERG and P. EDSTRÖM

Effect of Moisture on Paper Color

SHAKESPEARE TARJA and SHAKESPEARE JOHN

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Eugene Allen

Journal of the Optical Society of AmericaVol. 64,Issue 7,pp. 991-993(1974)

Spectrophotometric color formulation based on two-constant Kubelka-Munk theory

Eric Walowit

(1985). Thesis. Rochester Institute of Technology

Basic Equations Used in Computer Color Matching 

Eugene Allen

Journal of the Optical Society of AmericaVol. 56,Issue 9,pp. 1256-1259(1966)

https://www.osapublishing.org/josa/abstract.cfm?uri=josa-56-9-1256

Computer-Aided Color Formulation (How to Formulate Color)

Posted March 02, 2017 by Mike Huda

Xrite

https://www.xrite.com/blog/computer-aided-color-formulation

COMIC: An Analog Computer in the Colorant Industry

July-Sept. 2014, pp. 4-18, vol. 36

Computer

https://www.computer.org/csdl/magazine/an/2014/03/man2014030004/13rRUx0Pqrq

An investigation of the optical scattering and absorption coefficients of dyed handsheets and the application of the ICI system of color specification to these handsheets

Foote, William J. (William John)

1938 PhD Thesis IPC

https://smartech.gatech.edu/handle/1853/5491

NUMERICAL ANALYSIS OF THE INFLUENCE OF FORMATION ON THE OPTICAL PROPERTIES OF PAPER

DOUGLAS WAHREN

FEBRUARY, 1987 IPC Technical Paper 223

Mathematical Modelling of
Light Scattering in Paper and Print

Per Edström

PhD Thesis Mid Sweden University Sweden 2004

A Comparison Between the Coefficients of the Kubelka-Munk and DORT2002 Models

Per Edström
Mid Sweden University 2003

Simulation and modeling of light scattering in paper and print applications

Edström P. (2010)

In: Kokhanovsky A. (eds) Light Scattering Reviews 5. Springer Praxis Books. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10336-0_10

https://link.springer.com/chapter/10.1007/978-3-642-10336-0_10

Measuring and Modelling Light Scattering in Paper

Niklas Johansson

Department of Natural Sciences Mid Sweden University

Doctoral Thesis No. 224 O ̈ rnsko ̈ ldsvik, Sweden 2015

Does the photon-diffusion coefficient depend on absorption?

T. Durduran and A. G. Yodh

B. Chance

D. A. Boas

J. Opt. Soc. Am. A/Vol. 14, No. 12/December 1997