Adaptive transform coding of images based on removing just noticeable distortion

Chun-Hsien Chou

doi:10.1117/12.206769

21 April 1995 Adaptive transform coding of images based on removing just noticeable distortion

Chun-Hsien Chou

Proceedings Volume 2501, Visual Communications and Image Processing '95; (1995) https://doi.org/10.1117/12.206769
Event: Visual Communications and Image Processing '95, 1995, Taipei, Taiwan

Abstract

The removal of perceptual redundancy from image signals has been considered as a promising approach to maintain high image quality at low bit rates, and has recently become an important area of research. In this paper, a perceptually tuned discrete cosine transform (DCT) coder of gray-scale images is presented, where a just-noticeable distortion (JND) profile is measured as the perceptual redundancy inherent in an image. The JND profile provides each signal being coded with a visibility threshold of distortion, below which reconstruction errors are rendered imperceptible. By exploiting basic characteristics of human visual perception, the JND profile is derived from analyzing local properties of image signals. According to the sensitivity of human visual perception to spatial frequency, a distortion allocation algorithm is applied to each block for screening out perceptually unimportant coefficients (PUC's) and, simultaneously, determining quantizer stepsizes of perceptually important coefficients (PIC's). Simulation results show that high visual quality can be obtained at low bit rates, and, for a given bit rate, the visual quality of the images compressed by the proposed coder is more acceptable than those compressed by ISO-JPEG coder.

Citation Download Citation

Chun-Hsien Chou "Adaptive transform coding of images based on removing just noticeable distortion", Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); https://doi.org/10.1117/12.206769

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