Newton's Conclusions
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Chapter 6 COLOR and COLOR VISION
Chapter 6 – page 1 You need to learn the concepts and formulae highlighted in red. The rest of the text is for your intellectual enjoyment, but is not a requirement for homework or exams. Chapter 6 COLOR AND COLOR VISION COLOR White light is a mixture of lights of different wavelengths. If you break white light from the sun into its components, by using a prism or a diffraction grating, you see a sequence of colors that continuously vary from red to violet. The prism separates the different colors, because the index of refraction n is slightly different for each wavelength, that is, for each color. This phenomenon is called dispersion. When white light illuminates a prism, the colors of the spectrum are separated and refracted at the first as well as the second prism surface encountered. They are deflected towards the normal on the first refraction and away from the normal on the second. If the prism is made of crown glass, the index of refraction for violet rays n400nm= 1.59, while for red rays n700nm=1.58. From Snell’s law, the greater n, the more the rays are deflected, therefore violet rays are deflected more than red rays. The infinity of colors you see in the real spectrum (top panel above) are called spectral colors. The second panel is a simplified version of the spectrum, with abrupt and completely artificial separations between colors. As a figure of speech, however, we do identify quite a broad range of wavelengths as red, another as orange and so on. -
Computer Graphicsgraphics -- Weekweek 1212
ComputerComputer GraphicsGraphics -- WeekWeek 1212 Bengt-Olaf Schneider IBM T.J. Watson Research Center Questions about Last Week ? Computer Graphics – Week 12 © Bengt-Olaf Schneider, 1999 Overview of Week 12 Graphics Hardware Output devices (CRT and LCD) Graphics architectures Performance modeling Color Color theory Color gamuts Gamut matching Color spaces (next week) Computer Graphics – Week 12 © Bengt-Olaf Schneider, 1999 Graphics Hardware: Overview Display technologies Graphics architecture fundamentals Many of the general techniques discussed earlier in the semester were developed with hardware in mind Close similarity between software and hardware architectures Computer Graphics – Week 12 © Bengt-Olaf Schneider, 1999 Display Technologies CRT (Cathode Ray Tube) LCD (Liquid Crystal Display) Computer Graphics – Week 12 © Bengt-Olaf Schneider, 1999 CRT: Basic Structure (1) Top View Vertical Deflection Collector Control Grid System Electrode Phosphor Electron Beam Cathode Electron Lens Horizontal Deflection System Computer Graphics – Week 12 © Bengt-Olaf Schneider, 1999 CRT: Basic Structure (2) Deflection System Typically magnetic and not electrostatic Reduces the length of the tube and allows wider Vertical Deflection Collector deflection angles Control Grid System Electrode Phosphor Phospor Electron Beam Cathode Electron Lens Horizontal Fluorescence: Light emitted Deflection System after impact of electrons Persistence: Duration of emission after beam is turned off. Determines flicker properties of the CRT. Computer Graphics – Week -
Method for Compensating for Color Differences Between Different Images of a Same Scene
(19) TZZ¥ZZ__T (11) EP 3 001 668 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 30.03.2016 Bulletin 2016/13 H04N 1/60 (2006.01) (21) Application number: 14306471.5 (22) Date of filing: 24.09.2014 (84) Designated Contracting States: (72) Inventors: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB • Sheikh Faridul, Hasan GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO 35576 CESSON-SÉVIGNÉ (FR) PL PT RO RS SE SI SK SM TR • Stauder, Jurgen Designated Extension States: 35576 CESSON-SÉVIGNÉ (FR) BA ME • Serré, Catherine 35576 CESSON-SÉVIGNÉ (FR) (71) Applicants: • Tremeau, Alain • Thomson Licensing 42000 SAINT-ETIENNE (FR) 92130 Issy-les-Moulineaux (FR) • CENTRE NATIONAL DE (74) Representative: Browaeys, Jean-Philippe LA RECHERCHE SCIENTIFIQUE -CNRS- Technicolor 75794 Paris Cedex 16 (FR) 1, rue Jeanne d’Arc • Université Jean Monnet de Saint-Etienne 92443 Issy-les-Moulineaux (FR) 42023 Saint-Etienne Cedex 2 (FR) (54) Method for compensating for color differences between different images of a same scene (57) The method comprises the steps of: - for each combination of a first and second illuminants, applying its corresponding chromatic adaptation matrix to the colors of a first image to compensate such as to obtain chromatic adapted colors forming a chromatic adapted image and calculating the difference between the colors of a second image and the chromatic adapted colors of this chromatic adapted image, - retaining the combination of first and second illuminants for which the corresponding calculated difference is the smallest, - compensating said color differences by applying the chromatic adaptation matrix corresponding to said re- tained combination to the colors of said first image. -
Book of Abstracts of the International Colour Association (AIC) Conference 2020
NATURAL COLOURS - DIGITAL COLOURS Book of Abstracts of the International Colour Association (AIC) Conference 2020 Avignon, France 20, 26-28th november 2020 Sponsored by le Centre Français de la Couleur (CFC) Published by International Colour Association (AIC) This publication includes abstracts of the keynote, oral and poster papers presented in the International Colour Association (AIC) Conference 2020. The theme of the conference was Natural Colours - Digital Colours. The conference, organised by the Centre Français de la Couleur (CFC), was held in Avignon, France on 20, 26-28th November 2020. That conference, for the first time, was managed online and onsite due to the sanitary conditions provided by the COVID-19 pandemic. More information in: www.aic2020.org. © 2020 International Colour Association (AIC) International Colour Association Incorporated PO Box 764 Newtown NSW 2042 Australia www.aic-colour.org All rights reserved. DISCLAIMER Matters of copyright for all images and text associated with the papers within the Proceedings of the International Colour Association (AIC) 2020 and Book of Abstracts are the responsibility of the authors. The AIC does not accept responsibility for any liabilities arising from the publication of any of the submissions. COPYRIGHT Reproduction of this document or parts thereof by any means whatsoever is prohibited without the written permission of the International Colour Association (AIC). All copies of the individual articles remain the intellectual property of the individual authors and/or their -
International Journal for Scientific Research & Development
IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 12, 2014 | ISSN (online): 2321-0613 Modifying Image Appearance for Improvement in Information Gaining For Colour Blinds Prof.D.S.Khurge1 Bhagyashree Peswani2 1Professor, ME2, 1, 2 Department of Electronics and Communication, 1,2L.J. Institute of Technology, Ahmedabad Abstract--- Color blindness is a color perception problem of Light transmitted by media i.e., Television uses additive human eye to distinguish colors. Persons who are suffering color mixing with primary colors of red, green, and blue, from color blindness face many problem in day to day life each of which is stimulating one of the three types of the because many information are contained in color color receptors of eyes with as little stimulation as possible representations like traffic light, road signs etc. of the other two. Its called "RGB" color space. Mixtures of Daltonization is a procedure for adapting colors in an image light are actually a mixture of these primary colors and it or a sequence of images for improving the color perception covers a huge part of the human color space and thus by a color-deficient viewer. In this paper, we propose a re- produces a large part of human color experiences. That‟s coloring algorithm to improve the accessibility for the color because color television sets or color computer monitors deficient viewers. In Particular, we select protanopia, a type needs to produce mixtures of primary colors. of dichromacy where the patient does not naturally develop Other primary colors could in principle be used, but the “Red”, or Long wavelength, cones in his or her eyes. -
Application of Contrast Sensitivity Functions in Standard and High Dynamic Range Color Spaces
https://doi.org/10.2352/ISSN.2470-1173.2021.11.HVEI-153 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Color Threshold Functions: Application of Contrast Sensitivity Functions in Standard and High Dynamic Range Color Spaces Minjung Kim, Maryam Azimi, and Rafał K. Mantiuk Department of Computer Science and Technology, University of Cambridge Abstract vision science. However, it is not obvious as to how contrast Contrast sensitivity functions (CSFs) describe the smallest thresholds in DKL would translate to thresholds in other color visible contrast across a range of stimulus and viewing param- spaces across their color components due to non-linearities such eters. CSFs are useful for imaging and video applications, as as PQ encoding. contrast thresholds describe the maximum of color reproduction In this work, we adapt our spatio-chromatic CSF1 [12] to error that is invisible to the human observer. However, existing predict color threshold functions (CTFs). CTFs describe detec- CSFs are limited. First, they are typically only defined for achro- tion thresholds in color spaces that are more commonly used in matic contrast. Second, even when they are defined for chromatic imaging, video, and color science applications, such as sRGB contrast, the thresholds are described along the cardinal dimen- and YCbCr. The spatio-chromatic CSF model from [12] can sions of linear opponent color spaces, and therefore are difficult predict detection thresholds for any point in the color space and to relate to the dimensions of more commonly used color spaces, for any chromatic and achromatic modulation. -
A Novel Technique for Modification of Images for Deuteranopic Viewers
ISSN (Online) 2278-1021 IJARCCE ISSN (Print) 2319 5940 International Journal of Advanced Research in Computer and Communication Engineering Vol. 5, Issue 4, April 2016 A Novel Technique for Modification of Images for Deuteranopic Viewers Jyoti D. Badlani1, Prof. C.N. Deshmukh 2 PG Student [Dig Electronics], Dept. of Electronics & Comm. Engineering, PRMIT&R, Badnera, Amravati, Maharashtra, India1 Professor, Dept. of Electronics & Comm. Engineering, PRMIT&R, Badnera, Amravati, Maharashtra, India2 Abstract: About 8% of men and 0.5% women in world are affected by the Colour Vision Deficiency. As per the statistics, there are nearly 200 million colour blind people in the world. Color vision deficient people are liable to missing some information that is taken by color. People with complete color blindness can only view things in white, gray and black. Insufficiency of color acuity creates many problems for the color blind people, from daily actions to education. Color vision deficiency, is a condition in which the affected individual cannot differentiate between colors as well as individuals without CVD. Colour vision deficiency, predominantly caused by hereditary reasons, while, in some rare cases, is believed to be acquired by neurological injuries. A colour vision deficient will miss out certain critical information present in the image or video. But with the aid of Image processing, many methods have been developed that can modify the image and thus making it suitable for viewing by the person suffering from CVD. Color adaptation tools modify the colors used in an image to improve the discrimination of colors for individuals with CVD. This paper enlightens some previous research studies in this field and follows the advancement that has occurred over the time. -
Radiometry of Light Emitting Diodes Table of Contents
TECHNICAL GUIDE THE RADIOMETRY OF LIGHT EMITTING DIODES TABLE OF CONTENTS 1.0 Introduction . .1 2.0 What is an LED? . .1 2.1 Device Physics and Package Design . .1 2.2 Electrical Properties . .3 2.2.1 Operation at Constant Current . .3 2.2.2 Modulated or Multiplexed Operation . .3 2.2.3 Single-Shot Operation . .3 3.0 Optical Characteristics of LEDs . .3 3.1 Spectral Properties of Light Emitting Diodes . .3 3.2 Comparison of Photometers and Spectroradiometers . .5 3.3 Color and Dominant Wavelength . .6 3.4 Influence of Temperature on Radiation . .6 4.0 Radiometric and Photopic Measurements . .7 4.1 Luminous and Radiant Intensity . .7 4.2 CIE 127 . .9 4.3 Spatial Distribution Characteristics . .10 4.4 Luminous Flux and Radiant Flux . .11 5.0 Terminology . .12 5.1 Radiometric Quantities . .12 5.2 Photometric Quantities . .12 6.0 References . .13 1.0 INTRODUCTION Almost everyone is familiar with light-emitting diodes (LEDs) from their use as indicator lights and numeric displays on consumer electronic devices. The low output and lack of color options of LEDs limited the technology to these uses for some time. New LED materials and improved production processes have produced bright LEDs in colors throughout the visible spectrum, including white light. With efficacies greater than incandescent (and approaching that of fluorescent lamps) along with their durability, small size, and light weight, LEDs are finding their way into many new applications within the lighting community. These new applications have placed increasingly stringent demands on the optical characterization of LEDs, which serves as the fundamental baseline for product quality and product design. -
Got Good Color? Controlling Color Temperature in Imaging Software
Got Good Color? Controlling Color Temperature in Imaging Software When you capture an image of a specimen, you want it to look like what you saw through the eyepieces. In this article we will cover the basic concepts of color management and what you can do to make sure what you capture is as close to what you see as possible. Get a Reference Let’s define what you want to achieve: you want the image you produce on your computer screen or on the printed page to look like what you see through the eyepieces of your microscope. In order to maximize the match between these images, your system must be setup to use the same reference. White light is the primary reference that you have most control of in your imaging system. It is your responsibility to set it properly at different points in your system. Many Colors of White Although “White” sounds like a defined color, there are different shades of white. This happens because white light is made up of all wavelengths in the visible spectrum. True white light has an equal intensity at every wavelength. If any wavelength has a higher intensity than the rest, the light takes on a hue related to the dominant wavelength. A simple definition of the hue cast of white light is called “Color Temperature”. This comes from its basis in the glow of heated materials. In general the lower the temperature (in °Kelvin = C° + 273) the redder the light, the higher the temperature the bluer the light. The one standard white lighting in photography and photomicrography is 5000°K (D50) and is called daylight neutral white. -
Prepared by Dr.P.Sumathi COLOR MODELS
UNIT V: Colour models and colour applications – properties of light – standard primaries and the chromaticity diagram – xyz colour model – CIE chromaticity diagram – RGB colour model – YIQ, CMY, HSV colour models, conversion between HSV and RGB models, HLS colour model, colour selection and applications. TEXT BOOK 1. Donald Hearn and Pauline Baker, “Computer Graphics”, Prentice Hall of India, 2001. Prepared by Dr.P.Sumathi COLOR MODELS Color Model is a method for explaining the properties or behavior of color within some particular context. No single color model can explain all aspects of color, so we make use of different models to help describe the different perceived characteristics of color. 15-1. PROPERTIES OF LIGHT Light is a narrow frequency band within the electromagnetic system. Other frequency bands within this spectrum are called radio waves, micro waves, infrared waves and x-rays. The below figure shows the frequency ranges for some of the electromagnetic bands. Each frequency value within the visible band corresponds to a distinct color. The electromagnetic spectrum is the range of frequencies (the spectrum) of electromagnetic radiation and their respective wavelengths and photon energies. Spectral colors range from the reds through orange and yellow at the low-frequency end to greens, blues and violet at the high end. Since light is an electromagnetic wave, the various colors are described in terms of either the frequency for the wave length λ of the wave. The wavelength and frequency of the monochromatic wave is inversely proportional to each other, with the proportionality constants as the speed of light C where C = λ f. -
Digital Color Processing
Lecture 6 in Computerized Image Analysis Digital Color Processing Lecture 6 in Computerized Image Analysis Digital Color Processing Hamid Sarve [email protected] Reading instructions: Chapter 6 The slides 1 Lecture 6 in Computerized Image Analysis Digital Color Processing Electromagnetic Radiation Visible light (for humans) is electromagnetic radiation with wavelengths in the approximate interval of 380- 780 nm Gamma Xrays UV IR μWaves TV Radio 0.001 nm 10 nm 0.01 m VISIBLE LIGHT 400 nm 500 nm 600 nm 700 nm 2 2 Lecture 6 in Computerized Image Analysis Digital Color Processing Light Properties Illumination Achromatic light - “White” or uncolored light that contains all visual wavelengths in a “complete mix”. Chromatic light - Colored light. Monochromatic light - A single wavelength, e.g., a laser. Reflection No color that we “see” consists of only one wavelength The dominating wavelength reflected by an object decides the “color tone” or hue. If many wavelengths are reflected in equal amounts, an object appears gray. 3 3 Lecture 6 in Computerized Image Analysis Digital Color Processing The Human Eye Rods and Cones rods (stavar och tappar) only rods cone mostly cones only rods optical nerves 4 4 Lecture 6 in Computerized Image Analysis Digital Color Processing The Rods Approx. 100 million rod cells per eye Light-sensitive receptors Used for night-vision Not used for color-vision! Rods have a slower response time compared to cones, i.e. the frequency of its temporal sampling is lower 5 5 Lecture 6 in Computerized Image Analysis Digital Color -
Dark Image Enhancement Using Perceptual Color Transfer
IEEE Access, vol. 5, 2017, pp. 1-1. Dark image enhancement using perceptual color transfer. Cepeda-Negrete, J., Sanchez-Yanez, RE., Correa-Tome, Fernando E y Lizarraga-Morales, Rocio A. Cita: Cepeda-Negrete, J., Sanchez-Yanez, RE., Correa-Tome, Fernando E y Lizarraga-Morales, Rocio A (2017). Dark image enhancement using perceptual color transfer. IEEE Access, 5 1-1. Dirección estable: https://www.aacademica.org/jcepedanegrete/14 Esta obra está bajo una licencia de Creative Commons. Para ver una copia de esta licencia, visite http://creativecommons.org/licenses/by-nc-nd/4.0/deed.es. Acta Académica es un proyecto académico sin fines de lucro enmarcado en la iniciativa de acceso abierto. Acta Académica fue creado para facilitar a investigadores de todo el mundo el compartir su producción académica. Para crear un perfil gratuitamente o acceder a otros trabajos visite: http://www.aacademica.org. Received September 21, 2017, accepted October 13, 2017. Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000. Digital Object Identifier 10.1109/ACCESS.2017.2763898 Dark Image Enhancement Using Perceptual Color Transfer JONATHAN CEPEDA-NEGRETE 1, RAUL E. SANCHEZ-YANEZ 2, (Member, IEEE), FERNANDO E. CORREA-TOME2, AND ROCIO A. LIZARRAGA-MORALES3, (Member, IEEE) AQ:1 1Department of Agricultural Engineering, University of Guanajuato DICIVA, Guanajuato 36500 , Mexico 2Department of Electronics Engineering, University of Guanajuato DICIS, Guanajuato 36500, Mexico 3Department of Multidisciplinary Studies, University of Guanajuato DICIS, Guanajuato 36500, Mexico Corresponding author: Raul E. Sanchez-Yanez ([email protected]) The work of J. Cepeda-Negrete was supported by the Mexican National Council on Science and Technology (CONACyT) through the Scholarship 290747 under Grant 388681/254884.