In this paper, a new direction for Vector Quantization is proposed. To reduce the blocky effect and edge degradation, we combine Peano Scan and VQ (PSVQ) to achieve this goal in our implementation. All training images (512×512) are reordered to 1D space by efficient Peano Scan in advance. We classify 4 different partition segments including 1×8, 1×16, 1×32, and 1×64 dimensions according to the difference between the maximum and the minimum intensities in the 1D segment. Simulation results show that the performance of the suggested scheme is superior to the normal VQ scheme in the sense of PSNR, and both the edge degradation and the blocky effect is reduced.
|Number of pages||4|
|Journal||Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an|
|Publication status||Published - 2000 Jan 1|
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