Gradient match and side match fractal vector quantizers for images

In this paper, we propose gradient match fractal vector quantizers (GMFVQs) and side match fractal vector quantizers (SMFVQs), which are two classes of finite state fractal vector quantizers (FSFVQs), for the image coding framework. In our previous work, we proposed the noniterative fractal block coding (FBC) technique to improve the decoding speed and the coding performance for conventional FBC techniques. To reduce the number of bits for denoting the fractal code of the range block, the concepts of the gradient match vector quantizers (GMVQs) and the side match vector quantizers (SMVQs) are employed to the noniterative FBC technique. Unlike ordinary vector quantizers, the super codebooks in the proposed GMFVQs and SMFVQs are generated from the affine-transformed domain blocks in the noniterative FBC technique. The codewords in the state codebook are dynamically extracted from the super codebook with the side-match and gradient-match criteria. The redundancy in the affine-transformed domain blocks is greatly reduced and the compression ratio can be significantly increased. Our simulation results show that 15%-20% of the bit rates in the noniterative FBC technique are saved by using the proposed GMFVQs.

[1]  Hsuan T. Chang,et al.  Adaptive Schemes for Improving Fractal Block Coding of Images , 1999, J. Inf. Sci. Eng..

[2]  Hsuan-Ting Chang,et al.  Gradient match vector quantizers for images , 2000 .

[3]  Hsuan T. Chang,et al.  Iteration-free fractal image coding based on efficient domain pool design , 2000, IEEE Trans. Image Process..

[4]  Hsuan T. Chang,et al.  A Novel Non-Iterative Scheme for Fractal Image Coding , 2001, J. Inf. Sci. Eng..

[5]  Michel Barlaud,et al.  Fractal image compression based on Delaunay triangulation and vector quantization , 1996, IEEE Trans. Image Process..

[6]  Hsuan T. Chang,et al.  Finite-state fractal block coding of images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[7]  K. A. Saadi,et al.  Hybrid approach for still image compression based on fractal approximation and vector quantization , 1998, IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200).

[8]  Sang Uk Lee,et al.  A fractal vector quantizer for image coding , 1998, IEEE Trans. Image Process..

[9]  Dietmar Saupe,et al.  Combining fractal image compression and vector quantization , 2000, IEEE Trans. Image Process..

[10]  Jia-Shung Wang,et al.  Three-sided side match finite-state vector quantization , 2000, IEEE Trans. Circuits Syst. Video Technol..

[11]  Taejeong Kim,et al.  Side match and overlap match vector quantizers for images , 1992, IEEE Trans. Image Process..

[12]  Rae-Hong Park,et al.  Still image coding based on vector quantization and fractal approximation , 1996, IEEE Trans. Image Process..

[13]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[14]  Y. Fisher.  Fractal image compression: theory and application , 1995 .

[15]  Thanos Stouraitis,et al.  Image coding using a fractal/vector quantization model , 1997, Proceedings of 13th International Conference on Digital Signal Processing.

[16]  Hsuan-Ting Chang,et al.  Fractal block coding using a simplified finite-state algorithm , 1995, Other Conferences.

[17]  Chin-Chen Chang,et al.  A new image coding algorithm using variable-rate side-match finite-state vector quantization , 1997, IEEE Trans. Image Process..