Toward Perception-Based Image Retrieval
CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Compressed Image Quality Evaluation using Power Law Models
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Sampling and processing of color signals
IEEE Transactions on Image Processing
RGB calibration for color image analysis in machine vision
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Comparison and optimization of methods of color image quantization
IEEE Transactions on Image Processing
Recovering colors in an image with chromatic illuminant
IEEE Transactions on Image Processing
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Color space dimensionality possesses main problem in fast processing of color images so appropriate sampling of color images is very important. Unlike the existing statistical sampling algorithm, in this paper, a biologically inspired non-linear color image sampling technique has been proposed using non-uniform quantization of RGB space. Response of human retinal receptors to various light intensities is non-linear in nature. Buschbaum has qualitatively presented the non-linear tan-sigmoid model of the human vision as against the logarithmic and power law models. An experiment has been carried out on certified normal color vision observers in broad day light conditions to model their color vision. Readings of this experiment were used to compute the parameters of Red, Green and Blue color vision non-linearity presented by Buchsbaum. These parametric non-linearity equations were used to sample the color images and other applications of the work have been proposed. The non-linearity equations with respective parameters represent the models of Red, Green and Blue color vision receptors. Physiological limitations and facts of human vision have been utilized to compute the parameter.