Image vector quantization with variable dimension blocks and edge preserving cost function

This paper proposes a vector quantization scheme that uses variable vector dimensions and improves the perceived quality of the reconstructed images by using an edge based cost function. The cost function used for encoding is modified to take into account the number of edge pixels in a particular en...

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Bibliographic Details
Published in:Signal processing 2003-08, Vol.83 (8), p.1823-1826
Main Authors: Selvi, S.Sethu, Makur, Anamitra
Format: Article
Language:English
Subjects:
Applied sciences
Edge based coding
Exact sciences and technology
Image processing
Information, signal and communications theory
Pattern recognition
Perceptual image coding
Sampling, quantization
Signal and communications theory
Signal processing
Telecommunications and information theory
Vector quantization
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Summary:This paper proposes a vector quantization scheme that uses variable vector dimensions and improves the perceived quality of the reconstructed images by using an edge based cost function. The cost function used for encoding is modified to take into account the number of edge pixels in a particular encoding block. For a better subjective quality, the product of the fraction of the edge pixels and the fraction of the non-edge pixels should be minimized. This is included in the additive cost function of VQ and minimized as an unconstrained problem. This edge based VQ technique reduces edge artifacts like jagging, ringing and also VQ distortions that happen near object contours, thus improving the overall subjective quality of the reconstructed image.
ISSN:0165-1684
1872-7557
DOI:10.1016/S0165-1684(03)00117-8