Color image fidelity metrics evaluated using image distortion maps
Signal Processing - Special issue on image and video quality metrics
Color image quality metric S-CIELAB and its application on halftone texture visibility
COMPCON '97 Proceedings of the 42nd IEEE International Computer Conference
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Towards video quality metrics based on colour fractal geometry
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Full-Reference Image Quality Metrics: Classification and Evaluation
Foundations and Trends® in Computer Graphics and Vision
Color fractal structure model for reduced-reference colorful image quality assessment
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
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We describe a framework for quantifying color image distortion based on an adaptive signal decomposition. Specifically, local blocks of the image error are decomposed using a set of spatiochromatic basis functions that are adapted to the spatial and color structure of the original image. The adaptive functions are chosen to isolate specific distortions such as luminance, hue, and saturation changes. These adaptive basis functions are used to augment a generic orthonormal basis, and the overall distortion is computed from the weighted sum of the coefficients of the resulting overcomplete decomposition, with smaller weights chosen for the adaptive terms. A set of preliminary experiments show that the proposed distortion measure is consistent with human perception of color images subjected to a variety of different common distortions. The framework may be easily extended to include any form of continuous spatio-chromatic distortion.