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Claudio Oleari - One of the best experts on this subject based on the ideXlab platform.
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performance of a color difference formula based on osa ucs space using small medium color differences
Journal of The Optical Society of America A-optics Image Science and Vision, 2006Co-Authors: Rafael Huertas, Manuel Melgosa, Claudio OleariAbstract:An investigation of the color metrics and the complexity of the CIEDE2000 formula shows that CIELAB space is inadequate to represent small-medium color differences. The OSA-UCS (Uniform Color Space) Committee has shown that no space with uniform scale for large color differences exists. Therefore the practical way for color-difference specification is a color-difference formula in a nonuniform space. First, the BFD (Bradford University) ellipses are considered in the OSA-UCS space, and their very high regularity suggests a new and very simple color-difference formula at constant Luminance. Then the COM (combined) data set used for the development of the CIEDE2000 formula is considered in the OSA-UCS space, and the color-difference formula is extended to sample pairs with a different Luminance Factor. The value of the performance Factor PF/3 for the proposed OSA-UCS-based formula shows that the formula performs like the more complex CIEDE2000 formula for small-medium color differences.
Rafael Huertas - One of the best experts on this subject based on the ideXlab platform.
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performance of a color difference formula based on osa ucs space using small medium color differences
Journal of The Optical Society of America A-optics Image Science and Vision, 2006Co-Authors: Rafael Huertas, Manuel Melgosa, Claudio OleariAbstract:An investigation of the color metrics and the complexity of the CIEDE2000 formula shows that CIELAB space is inadequate to represent small-medium color differences. The OSA-UCS (Uniform Color Space) Committee has shown that no space with uniform scale for large color differences exists. Therefore the practical way for color-difference specification is a color-difference formula in a nonuniform space. First, the BFD (Bradford University) ellipses are considered in the OSA-UCS space, and their very high regularity suggests a new and very simple color-difference formula at constant Luminance. Then the COM (combined) data set used for the development of the CIEDE2000 formula is considered in the OSA-UCS space, and the color-difference formula is extended to sample pairs with a different Luminance Factor. The value of the performance Factor PF/3 for the proposed OSA-UCS-based formula shows that the formula performs like the more complex CIEDE2000 formula for small-medium color differences.
R W G Hunt - One of the best experts on this subject based on the ideXlab platform.
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dynamic cone response functions for models of colour appearance
Color Research and Application, 2003Co-Authors: R W G Hunt, M R LuoAbstract:The CIECAM97s type of colour appearance models results in some changes in hue and saturation for series of colours of constant chromaticity but changing Luminance Factor. To keep hue and saturation constant for such series, a model in which the dynamic cone response is based on a power function has been developed. By optimizing its parameters, its correlates of hue, lightness, colourfulness, brightness, and saturation perform nearly as well as those of CIECAM97s. A similar performance is achieved in a modified power model, which is more physiologically plausible. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 82–88, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10128
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the ciecam02 color appearance model
Color Imaging Conference, 2002Co-Authors: Nathan Moroney, R W G Hunt, Mark D Fairchild, Ronnier M Luo, Todd NewmanAbstract:The CIE Technical Committee 8-01, color appearance models for color management applications, has recently proposed a single set of revisions to the CIECAM97s color appearance model. This new model, called CIECAM02, is based on CIECAM97s but includes many revisions1-4 and some simplifications. A partial list of revisions includes a linear chromatic adaptation transform, a new non-linear response compression function and modifications to the calculations for the perceptual attribute correlates. The format of this paper is an annotated description of the forward equations for the model. Introduction The CIECAM02 color appearance model builds upon the basic structure and form of the CIECAM97s5,6 color appearance model. This document describes the single set of revisions to the CIECAM97s model that make up the CIECAM02 color appearance model. There were many, often conflicting, considerations such as compatibility with CIECAM97s, prediction performance, computational complexity, invertibility and other Factors. The format for this paper will differ from previous papers introducing a color appearance model. Often a general description of the model is provided, then discussion about its performance and finally the forward and inverse equations are listed separately in an appendix. Performance of the CIECAM02 model will be described elsewhere7 and for the purposes of brevity this paper will focus on the forward model. Specifically, this paper will attempt to document the decisions that went into the design of CIECAM02. For a complete description of the forward and inverse equations, as well as usage guidelines, interested readers are urged to refer to the TC 8-01 web site8 or to the CIE for the latest draft or final copy of the technical report. This paper is not intended to provide a definitive reference for implementing CIECAM02 but as an introduction to the model and a summary of its structure. Data Sets The CIECAM02 model, like CIECAM97s, is based primarily on a set corresponding colors experiments and a collection of color appearance experiments. The corresponding color data sets9,10 were used for the optimization of the chromatic adaptation transform and the D Factor. The LUTCHI color appearance data11,12 was the basis for optimization of the perceptual attribute correlates. Other data sets and spaces were also considered. The NCS system was a reference for the e and hue fitting. The chroma scaling was also compared to the Munsell Book of Color. Finally, the saturation equation was based heavily on recent experimental data.13 Summary of Forward Model A color appearance model14,15 provides a viewing condition specific means for transforming tristimulus values to or from perceptual attribute correlates. The two major pieces of this model are a chromatic adaptation transform and equations for computing correlates of perceptual attributes, such as brightness, lightness, chroma, saturation, colorfulness and hue. The chromatic adaptation transform takes into account changes in the chromaticity of the adopted white point. In addition, the Luminance of the adopted white point can influence the degree to which an observer adapts to that white point. The degree of adaptation or D Factor is therefore another aspect of the chromatic adaptation transform. Generally, between the chromatic adaptation transform and computing perceptual attributes correlates there is also a non-linear response compression. The chromatic adaptation transform and D Factor was derived based on experimental data from corresponding colors data sets. The non-linear response compression was derived based on physiological data and other considerations. The perceptual attribute correlates was derived by comparing predictions to magnitude estimation experiments, such as various phases of the LUTCHI data, and other data sets, such as the Munsell Book of Color. Finally the entire structure of the model is generally constrained to be invertible in closed form and to take into account a sub-set of color appearance phenomena. Viewing Condition Parameters It is convenient to begin by computing viewing condition dependent constants. First the surround is selected and then values for F, c and Nc can be read from Table 1. For intermediate surrounds these values can be linearly interpolated.2 Table. 1. Viewing condition parameters for different surrounds. Surround F c Nc Average 1.0 0.69 1.0 Dim 0.9 0.59 0.95 Dark 0.8 0.525 0.8 The value of FL can be computed using equations 1 and 2, where LA is the Luminance of the adapting field in cd/m2. Note that this two piece formula quickly goes to very small values for mesopic and scotopic levels and while it may resemble a cube-root function there are considerable differences between this two-piece function and a cube-root as the Luminance of the adapting field gets very small. ! k =1/ 5L A +1 ( ) (1) ! F L = 0.2k 4 5L A ( ) + 0.1 1" k4 ( ) 2 5L A ( ) 1/ 3 (2) The value n is a function of the Luminance Factor of the background and provides a very limited model of spatial color appearance. The value of n ranges from 0 for a background Luminance Factor of zero to 1 for a background Luminance Factor equal to the Luminance Factor of the adopted white point. The n value can then be used to compute Nbb, Ncb and z, which are then used during the computation of several of the perceptual attribute correlates. These calculations can be performed once for a given viewing condition.
C S Mccamy - One of the best experts on this subject based on the ideXlab platform.
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munsell value as explicit functions of cie Luminance Factor
Color Research and Application, 1992Co-Authors: C S MccamyAbstract:Equations are given to compute Munsell value from a CIE Luminance Factor Y. The equations are a very accurate, though not mathematically exact, inversion of the fifth-order equation adopted by the Optical Society of America as the practical definition of Munsell value. The maximum error in Munsell value is 0.0035. The equations have been employed by the Committee on Appearance of the American Society for Testing and Materials.
Manuel Melgosa - One of the best experts on this subject based on the ideXlab platform.
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performance of a color difference formula based on osa ucs space using small medium color differences
Journal of The Optical Society of America A-optics Image Science and Vision, 2006Co-Authors: Rafael Huertas, Manuel Melgosa, Claudio OleariAbstract:An investigation of the color metrics and the complexity of the CIEDE2000 formula shows that CIELAB space is inadequate to represent small-medium color differences. The OSA-UCS (Uniform Color Space) Committee has shown that no space with uniform scale for large color differences exists. Therefore the practical way for color-difference specification is a color-difference formula in a nonuniform space. First, the BFD (Bradford University) ellipses are considered in the OSA-UCS space, and their very high regularity suggests a new and very simple color-difference formula at constant Luminance. Then the COM (combined) data set used for the development of the CIEDE2000 formula is considered in the OSA-UCS space, and the color-difference formula is extended to sample pairs with a different Luminance Factor. The value of the performance Factor PF/3 for the proposed OSA-UCS-based formula shows that the formula performs like the more complex CIEDE2000 formula for small-medium color differences.
