A Spatial Color-Gamut Calculation to Optimize Color Appearance

Colorimetry is limited to image data from a single pixel. Measures of errors between an “original” and a “reproduction” are usually described as the distance between the two values of a pixel in a colorimetric three-dimensional space. Human color constancy uses spatial comparisons between different parts of the image. The relationships among neighboring pixels are far more important than the absolute differences between the colorimetric values of an original and its gamutlimited reproduction. If all the pixels in an image have a reproduction error in the same direction (red, green, blue, lightness, hue, chroma), then our color constancy mechanism helps to make large colorimetric errors appear small. However, if all the errors are randomly distributed, then small colorimetric errors appear large. This paper will describe experiments using constant colorimetric and appearance errors to produce variable quality of reproduction. Further, it describes a technique of calculating the best appearance image using spatial comparisons. This calculation will be applied to a color-gamut problem. This approach minimizes the spatial errors introduced by limited color gamut and employs human color constancy mechanisms, so as to reduce the color appearance differences caused by limited color gamut.