• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Lossless VQ Indices Compression Based on the High Correlation of Adjacent Image Blocks

Vol. 8, No.8, August 29, 2014
10.3837/tiis.2014.08.020, Download Paper (Free):

Abstract

Traditional vector quantization (VQ) schemes encode image blocks as VQ indices, in which there is significant similarity between the image block and the codeword of the VQ index. Thus, the method can compress an image and maintain good image quality. This paper proposes a novel lossless VQ indices compression algorithm to further compress the VQ index table. Our scheme exploits the high correlation of adjacent image blocks to search for the same VQ index with the current encoding index from the neighboring indices. To increase compression efficiency, codewords in the codebook are sorted according to the degree of similarity of adjacent VQ indices to generate a state codebook to find the same index with the current encoding index. Note that the repetition indices both on the search path and in the state codebooks are excluded to increase the possibility for matching the current encoding index. Experimental results illustrated the superiority of our scheme over other compression schemes in the index domain.


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Cite this article

[IEEE Style]
Zhi-Hui Wang, Hai-Rui Yang, Chin-Chen Chang, Gwoboa Horng and Ying-Hsuan Huang, "Lossless VQ Indices Compression Based on the High Correlation of Adjacent Image Blocks," KSII Transactions on Internet and Information Systems, vol. 8, no. 8, pp. 2913-2929, 2014. DOI: 10.3837/tiis.2014.08.020

[ACM Style]
Wang, Z., Yang, H., Chang, C., Horng, G., and Huang, Y. 2014. Lossless VQ Indices Compression Based on the High Correlation of Adjacent Image Blocks. KSII Transactions on Internet and Information Systems, 8, 8, (2014), 2913-2929. DOI: 10.3837/tiis.2014.08.020