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This paper presents a post-processing method for vector quantization that softens codewords to improve PSNR. It introduces a symmetric codeword softening technique and demonstrates the reconstruction of bad matching image blocks. Experimental results show improved image quality.
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A Post-Processing Vector Quantization Method Though Softening Codewords to Achieve a Higher PSNR Zhibin Pan, Koji Kotani and Tadahiro Ohmi International Symposium on Intelligent Signal Processing and Communication Systems pp. 37-41, November 2002 Speaker : HsinYu Lee Date: 2004/06/9
Introduction • TWO things are made clear after conventional VQ. • One thing is which codeword is nearest to the current image block (winner index). • The other is to what extent the nearness is reached (VQ distortion). • Conventionally, only the winner index is used while VQ distortion itself is ignored completely. • When original codebook is fixed, the bad matching is due to there are not sufficient codewords to represent the input image block very well.
MainConcept • Conventionally, codewords are hard in the meaning of pixel arrangement or codeword shape is unchangeable. • If some freedoms are given to a codeword, pixel arrangement or codeword shape can become changeable.
Example of Distortion Sorting Block Size:4 4 512 512 pixel, 8-bit gray-scale
Symmetric Codeword Softening Way Using 3-bit Freedom Original pixel arrangement {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16} Symmetric codeword softening
How to Reconstruct a Bad Matching Image Block • One winner index and one softening status, called main information, describer are needed. • Side information (flag) to show positions of the bad matching image blocks is also necessary to be transmitted. • Flag=0 by conventional VQ • Flag=1 by post-processing
ExperimentalResults Enlarged diagram of VQ distortion comparison before and after post-processing via codeword softening for the 5% worst matching image blocks.