Wavelet-based image compression using perceptual distortion metric

Hemen Goswami; Samuel Peter Kozaitis

doi:10.1117/12.484832

8 August 2003 Wavelet-based image compression using perceptual distortion metric

Hemen Goswami, Samuel Peter Kozaitis

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Proceedings Volume 5108, Visual Information Processing XII; (2003) https://doi.org/10.1117/12.484832
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Bits are allocated to various subbands to minimize a particular cost function to achieve compression in subband coding. The most common cost function is the L2 norm based on mean squared error (MSE). However, the MSE often fails to correspond to the perceptual quality of the image, especially at low bit rate. In this paper, we allocate bits into various subbands by minimizing the Minkowsky metric -- a commonly used perceptual distortion measure. We then design the quantizer for each subband independent of each other based on the allocated bits. Experimental results indicate improved perceptual quality for the compressed images using Minkowsky metric compared to that of using the MSE metric.

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Hemen Goswami and Samuel Peter Kozaitis "Wavelet-based image compression using perceptual distortion metric", Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003); https://doi.org/10.1117/12.484832

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