NDLI: Improving VQ Index Compression with Modified Relative Index Table

Content Provider	IEEE Xplore Digital Library
Author	Hung-Min Sun Bying-He Ku Chung-Chi Wu Ting-Yu Lin
Copyright Year	2010
Abstract	Image Vector Quantization (VQ) has many current applications, like speech and image compression, and envisioned applications, such as digital watermarking, data hiding and speaker identification. Given an image, VQ produce an index map by quantizing the image block by block. Recently, a loss less VQ index compression scheme, called Index Searching Algorithm with index Associated List (ISAIAL), was proposed to improve the VQ performance by using relative index table. The basic idea behind ISAIAL is to utilize the effect of correlation between adjacent indices in the index map. In this paper, two modified relative index tables are proposed to improve the performance of ISAIAL further. The computation of optimal size for modified relative index tables is also addressed. The proposed methods were evaluated via extensive experiments. The results show that the ISAIAL is improved by the proposed methods. Moreover, our approaches apparently reduce the bit rate as compared to the conventional VQ and some commercial loss less compressors, such as rar, zip and arj.
Starting Page	221
Ending Page	225
File Size	345772
Page Count	5
File Format	PDF
ISBN	9781424495955
DOI	10.1109/CDEE.2010.50
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Image coding Vector quantization Image Compression Bit rate Decoding Vector Quantization Indexes Search Order Coding Pixel Index Compression
Content Type	Text
Resource Type	Article

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