Image Compression Based on Side-Match VQ and SOC

A novel image compression scheme that takes advantages of side-match vector quantization (SMVQ) and search-order-coding (SOC) algorithm is proposed in this article. In the proposed scheme, the image to be compressed is firstly encoded into an index table by applying the traditional SMVQ compression...

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Bibliographic Details
Main Authors: Shih-Chieh Shie, Long-Tai Chen
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Bit rate
Clustering algorithms
Computer applications
Digital images
Image coding
image compression
Image storage
Iterative algorithms
Partitioning algorithms
search-order-coding
SMVQ
Vector quantization
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Summary:A novel image compression scheme that takes advantages of side-match vector quantization (SMVQ) and search-order-coding (SOC) algorithm is proposed in this article. In the proposed scheme, the image to be compressed is firstly encoded into an index table by applying the traditional SMVQ compression technique. Then, the index table of image is further compressed based on the ordinary SOC algorithm. To improve the compression efficiency of the proposed scheme, a modified search-order-coding algorithm, called left-upper-coding (LUC), is designed. The performance comparison between the two SOC algorithms has been conducted in our computer simulation. Experimental results show that the SOC algorithm functions very well with SMVQ, and the LUC algorithm is more feasible for compressing the SMVQ indexes of image when the computational efficiency is concerned.
DOI:10.1109/DICTA.2009.68