17 June 2003 Suprathreshold image compression based on contrast allocation and global precedence
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Visually lossless image compression algorithms aim to keep the compression-induced distortions below the threshold of visual detection, most-often by exploiting the fact that contrast sensitivity varies with spatial frequency. However, when an image is coded in a visually lossy manner, there is little evidence to suggest that visual quality is preserved by minimizing the compression-induced distortions. This paper presents a visually lossy wavelet image compression algorithm based on contrast allocations and visual global precedence: subbands are quantized such that the distortions in the reconstructed image exhibit specific root-mean squared contrast ratios, and such that edge structure is preserved across scale-space, with a preference for global spatial scales. A model which relates contrast (of the distortions) in the reconstructed image to mean-squared error in the wavelet subbands is derived and presented; this model provides an efficient means of adjusting contrast in the transform domain via traditional quantization techniques, thus allowing the algorithm to be used in a wide variety of coders.
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Damon M. Chandler, Damon M. Chandler, Sheila S. Hemami, Sheila S. Hemami, } "Suprathreshold image compression based on contrast allocation and global precedence", Proc. SPIE 5007, Human Vision and Electronic Imaging VIII, (17 June 2003); doi: 10.1117/12.477772; https://doi.org/10.1117/12.477772

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