This paper proposes a vector quantization scheme that uses variable vector dimensions and improves the perceived quality of the reconstructed images by using an edgebased cost function. The cost function used for enc...
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This paper proposes a vector quantization scheme that uses variable vector dimensions and improves the perceived quality of the reconstructed images by using an edgebased 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 edgebased 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. (C) 2003 Elsevier Science B.V. All rights reserved.
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