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Article type: Research Article
Authors: Chang, Chin-Chen | Chen, Guei-Mei | Hu, Yu-Chen
Affiliations: Department of Information Engineering and Computer Science, Feng Chia University, Taichung, Taiwan 407, R.O.C. E-mail: [email protected] | Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan 62107, R.O.C. E-mail: [email protected] | Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan 433, R.O.C. E-mail: [email protected]
Abstract: A novel method for the compression of the index table of vector quantization (VQ) is proposed in this paper. This method is designed based on the observation that neighboring image blocks are highly correlated. In other words, VQ-encoded neighboring image blocks tend to have similar indices if the codebook used in VQ is previously sorted by the principal component analysis technique. According to this characteristic, we find the same or similar indices around the current processing index to process it. In addition, the pre-statistics technique is employed to gather differences that appear most often in the index table. Simulation results indicate that the newly proposed scheme achieves significant reduction of bit rate without losing any image quality by the original VQ encoding.
Journal: Fundamenta Informaticae, vol. 71, no. 2-3, pp. 215-227, 2006
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