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A Novel Index Coding Scheme for Vector Quantization

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Języki publikacji
EN
Abstrakty
EN
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.
Słowa kluczowe
Wydawca
Rocznik
Strony
215--227
Opis fizyczny
fot., tab., wykr., bibliogr. 19 poz.
Twórcy
autor
autor
autor
  • Department of Information Engineering and Computer Science Feng Chia University, Taichung, Taiwan 407, R.O.C., ccc@cs.ccu.edu.tw
Bibliografia
  • [1] Akrout, N., Prost, R., Goutte, G.: Image Compression by Vector Quantization: a Review Focused on Codebook Generation, Image and Vision Computing, 12(10), 1994, 627-637.
  • [2] Chang, C. C., Lin, D. C., Chen, T. S.: An Improved VQ Codebook Search Algorithm Using Principal Component Analysis, Journal of Visual Communication and Image Representation, 8(1), 1997, 27-37.
  • [3] Chang, C. C., Sung, C. H., Chen, T. S.:A Locally Adaptive Scheme for Image Index Compression, Proceedings of the 1997 Conference on Computer Vision, Graphics, and Image Processing, Taichung, Taiwan, 1997, 93-99.
  • [4] Gray, M.: Vector Quantization, IEEE Transactions on Information Theory, 28,1982, 157-166.
  • [5] Gray, R. M., Gersho, A.: Vector Quantization and Signal Compression, Norwell, MA: Kluwer Academic Publishers, 1992.
  • [6] Hang, H. M.,Woods, J. M.: Predictive Vector Quantization of Images, IEEE Transactions on communications, 33, 1985, 1208-1279.
  • [7] Hsieh, C. H., Tsai, J. C.: Lossless Compression of VQ Index with Search-Order Coding, IEEE Transactions on Image Processing, 5(11), 1996, 1579-1582.
  • [8] Huffman, D. A.: A Method for the Construction of Minimum Redundancy Codes, in Proceedings of IRE, 40, 1952, 1098-1101.
  • [9] Lee, R. C. T., Chin, Y. H., Chang, S. C.: Application of Principal Component Analysis to Multikey Searching, IEEE Transactions on Software Engineering, SE-2(3), 1976, 185-193.
  • [10] Lo, K. T., Feng, J.: Predictive Mean Search Algorithms for Fast VQ Encoding of Images, IEEE Transactions on Consumer Electronics, 41(2), 1995, 327-331.
  • [11] Li, W., Zhang, Y. Q.: Vector-Based Signal Processing and Quantization for Image and Video Compression, Proceedings of the IEEE, 83(2), 1995, 317-335.
  • [12] Linde, Y., Buzo, A., Gray, R. M.: An Algorithm for Vector Quantizer Design, IEEE Transactions on Communications, 28, 1980, 84-95.
  • [13] Liu, E. C., Wang, T. C.: An Improvement on Lossless Compression of VQ Indices, Proceedings of the 1998 IEEE Global Telecommunications Conference GLOBECOM98 The Bridge to Global Integration, Sydney, Australia, 3, 1998, 1699-1704.
  • [14] Nasrabadi, N. M., Choo, C. Y., Feng, Y.: Dynamic Finite-State Vector Quantization, IEEE Transactions on Communications, 42(5), 1994, 2145-2154.
  • [15] Nasrabadi, N. M., Feng, Y.: Image Compression Using Address-Vector Quantization, IEEE Transactions on Communications, 38(12), 1990, 2166-2173.
  • [16] Shanbehzadeh, J., Ogunbona, P. O.: Index-Compressed Vector Quantization Based on Index Mapping, IEE Proceedings on Vision, Image and Signal Processing, 144, 1997, 31-38.
  • [17] Tsai, J. C., Hsieh, C. H., Hsu, T. C.: A New Dynamic Finite-State Vector Quantization Algorithm for Image Compression, IEEE Transactions on Image Processing, 9(11), 2000, 1825-1836.
  • [18] Jarvi, A., Lehtien, J., Nevalainen, O.: Variable Quality Image Compression System Based on SPIHT, Signal Processing: Image Communication, 14(9), 1999, 683-696.
  • [19] Said, A., Pearlman,W. A.: A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees, IEEE Transactions on Circuits and System for Video Technology, 6(3), 1996, 243-250.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS2-0010-0035
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