Imaging Components, Systems, and Processing

Refined codebook for grayscale image coding based on vector quantization

[+] Author Affiliations
Yu-Chen Hu, Wu-Lin Chen

Providence University, Department of Computer Science and Information Management, 200 Chung Chi Road, Taichung 43301, Taiwan

Pi-Yu Tsai

National United University, Department of Computer Science and Information Engineering, No. 1, Lienda, Miaoli 36003, Taiwan

Opt. Eng. 54(7), 073110 (Jul 27, 2015). doi:10.1117/1.OE.54.7.073110
History: Received March 25, 2015; Accepted June 22, 2015
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Abstract.  Vector quantization (VQ) is a commonly used technique for image compression. Typically, the common codebooks (CCBs) that are designed by using multiple training images are used in VQ. The CCBs are stored in the public websites such that their storage cost can be omitted. In addition to the CCBs, the private codebooks (PCBs) that are designed by using the image to be compressed can be used in VQ. However, calculating the bit rates (BRs) of VQ includes the storage cost of the PCBs. It is observed that some codewords in the CCB are not used in VQ. The codebook refinement process is designed to generate the refined codebook (RCB) based on the CCB of each image. To cut down the BRs, the lossless index coding process and the two-stage lossless coding process are employed to encode the index table and the RCB, respectively. Experimental results reveal that the proposed scheme (PS) achieves better image qualities than VQ with the CCBs. In addition, the PS requires less BRs than VQ with the PCBs.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Yu-Chen Hu ; Wu-Lin Chen and Pi-Yu Tsai
"Refined codebook for grayscale image coding based on vector quantization", Opt. Eng. 54(7), 073110 (Jul 27, 2015). ; http://dx.doi.org/10.1117/1.OE.54.7.073110


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