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Proceedings Paper

Perceptual coders and perceptual metrics
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Paper Abstract

We examine perceptual metrics and use them to evaluate the quality of still image coders. We show that mean-squared- error based metrics fail to predict image quality when one compares artifacts generated by different types of image coders. We consider three different types of coders: JPEG, the Safranek-Johnston perceptual subband coder (PIC), and the Said-Pearlman SPIHT algorithm with perceptually weighted subband quantization, based on the Watson et al. visual thresholds. We show that incorporating perceptual weighting in the SPIHT algorithm results in significant improvement in visual quality. The metrics we consider are based on the same image decompositions as the corresponding compression algorithms. Such metrics are computationally efficient and considerably simpler than more elaborate metrics. However, since each of the metrics is used for the optimization of a coder, one expects that they would be biased towards that coder. We use the metrics to evaluate the performance of the compression techniques for a wide range of bit rates. Our experiments indicate that the PIC metric provides the best correlation with subjective evaluations. It predicts that at very low bit rates the SPIHT algorithm and the 8 by 8 PIC coder perform the best, while at high bit rates the 4 by 4 PIC coder is the best. More importantly, we show that the relative algorithm performance depends on image content, with the subband and DCT coders performing best for images with a lot of high frequency content, and the wavelet coders performing best for smoother images.

Paper Details

Date Published: 8 June 2001
PDF: 13 pages
Proc. SPIE 4299, Human Vision and Electronic Imaging VI, (8 June 2001); doi: 10.1117/12.429485
Show Author Affiliations
Junqing Chen, Northwestern Univ. (United States)
Thrasyvoulos N. Pappas, Northwestern Univ. (United States)


Published in SPIE Proceedings Vol. 4299:
Human Vision and Electronic Imaging VI
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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