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Perceptually lossless image compression

Authors: P.J. Hahn; V.J. Mathews;

Perceptually lossless image compression

Abstract

Summary form only given. This paper presents an algorithm for perceptually lossless image compression. The approach utilizes properties of the human visual system in the form of a perceptual threshold function (PTF) model. The PTF model determines the amount of distortion that can be introduced at each location of the image. Thus, constraining all quantization errors to levels below the PTF results in perceptually lossless image compression. The system employs a modified form of the embedded zerotree wavelet (EZW) coding algorithm that limits the quantization errors of the wavelet transform coefficients to levels below those specified by the model of the perceptual threshold function. Experimental results demonstrate perceptually lossless compression of monochrome images at bit rates ranging from 0.4 to 1.2 bits per pixel at a viewing distance of six times the image height and at bit rates from 0.2 to 0.5 bits per pixel at a viewing distance of twelve times the image height.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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