Abstract
Under the consideration of computational complexity and design regularity, in this paper, a FASVQ (filtering and searching vector quantization) is presented to compress images. FASVQ utilizes a heuristic to filter codevectors with small costs and then employs full-search VQ within the surviving codevectors. We have proven that the proposed heuristic can easily be implemented by a table lookup technique and over 95% codevectors can be filtered. Although, the quantized codevector of FASVQ wouldn't be optimal, the experimental results show that the PSNR degradation between full-search VQ and FASVQ is only 0.24 dB on the average.
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Huang, SY. Filtering and Searching Vector Quantization. The Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology 35, 213–221 (2003). https://doi.org/10.1023/A:1023664902408
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DOI: https://doi.org/10.1023/A:1023664902408