Fractal image compression based on visual perception

Jer-Sen Chen

doi:10.1117/12.207530

20 April 1995 Fractal image compression based on visual perception

Jer-Sen Chen

Proceedings Volume 2411, Human Vision, Visual Processing, and Digital Display VI; (1995) https://doi.org/10.1117/12.207530
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

Self-similarities, commonly explored in fractal image compression, are usually translated into matches between two pools, the range and the domain blocks, which are different partitions of the same image to be encoded. Simple transformations on the domain blocks are used in order to obtain a better match. A root-mean-square error measure between a range block and a transformed domain block is used in the encoding process to quantify the performance of the matching process and subsequently the quality of the encoded imaged. Alternative measures can be used in fractal image compression to account for human visual perception. Simple strategies, such as block intensity weighting and block texture weighting, reduce perceptual degradation with only very little added computational cost. Weighted error measures in frequency domain, though computationally much more expensive, can provide a more natural model of visual perception such as the direct account for the contrast sensitivity function. A multiscale approach to encode the image details at different resolution is proposed to not only speed up the matching process between the range and the domain blocks but also provide a mechanism for multiscale representation.

Citation Download Citation

Jer-Sen Chen "Fractal image compression based on visual perception", Proc. SPIE 2411, Human Vision, Visual Processing, and Digital Display VI, (20 April 1995); https://doi.org/10.1117/12.207530

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