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Journal of Information Science and Engineering, Vol. 26 No. 3, pp. 1011-1027 (May 2010)

Hybrid Image Compression Based on Set-Partitioning Embedded Block Coder and Residual Vector Quantization

SHENG-FUU LIN, HSI-CHIN HSIN* AND CHIEN-KUN SU+
Department of Electrical and Control Engineering
National Chiao Tung University
Hsinchu, 300 Taiwan
*Department of Computer Science and Information Engineering
National United University
Miaoli, 360 Taiwan
+Department of Electrical Engineering
Chung Hua University
Hsinchu, 300 Taiwan

A hybrid image coding scheme based on the set-partitioning embedded block coder (SPECK) and residual vector quantization (RVQ) is proposed for image compression. In which, the scaling and wavelet coefficients of an image are coded by using the original SPECK algorithm and the SPECK with RVQ, respectively. The use of hybrid coding strategy by combining SPECK with RVQ for high frequency wavelet coefficients is to take account of the energy clustering property of wavelet transform. Experimental results show that, for gray-level still images, the proposed hybrid RVQ-SPECK coder outperforms SPECK, e.g. the peak-signal-to-noise-ratio (PSNR) values can be improved by 1.67 dB and 0.69 dB at compression rate of 1 bit per pixel for the 256 256 gray-level Lena and Barbra images, respectively. The application for chroma subsampling images is also presented in this paper, and the proposed method usually outperforms color SPECK method. The PSNR values can be improved by 1.11 dB for the Y plane, 0.99 dB for the U plane, and 2.31 dB for the V plane at the bit budget of 81,920 bits for the test image Goldhill. In addition to high coding efficiency, the proposed method also preserves the features of embeddedness, low decoding complexity, and exact bit-rate control.

Keywords: image compression, residual vector quantization (RVQ), set-partitioning embedded block coder (SPECK), chroma subsampling images, embeddedness

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Received July 8, 2008; revised November 20, 2008; accepted February 12, 2009.
Communicated by Liang-Gee Chen.