Vector quantization of images with variable block size

Applied Soft Computing Journal

Volumn 8, Issue 1, 2008, Pages 634-645

  Sasazaki, Kazuya ^a   Saga, Sato ^a   Maeda, Junji ^a   Suzuki, Yukinori ^a  

^a MURORAN INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

Discriminant analysis; Fuzzy k means; Image compression; Local fractal dimension; Variable block size; Vector quantization; Well perceived image

Indexed keywords

COMPUTATIONAL COMPLEXITY; DISCRIMINANT ANALYSIS; FRACTAL DIMENSION; IMAGE CLASSIFICATION; IMAGE QUALITY; SIGNAL TO NOISE RATIO;

CODEBOOK (CB); COMPRESSION RATE; FUZZY K MEANS; GENERALIZED LLOYD ALGORITHM (GLA); QUAD TREE (QT) DECOMPOSITION ALGORITHM; VARIABLE BLOCK SIZE;

VECTOR QUANTIZATION;

EID: 34548482728     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2007.05.002     Document Type: Article

References (27)

1. Tzovaras D., and Strintzis M.G. Use of nonlinear principal component analysis and vector quantization for image coding. IEEE Trans. Image Process. 7 8 (1998) 1218-1222
2. Karayiannis N.B., Pai P., and Zervos N. Image compression based on fuzzy algorithms for learning vector quantization and wavelet image decomposition. IEEE Trans. Image Process. 7 8 (1998) 1223-1230
3. Sayood K. Introduction to Data Compression (2000), Morgan Kaufmann Publisher, Boston
4. Fujibayashi M., Nozawa T., Nakayama T., Mochizuki K., Konda M., Kotani K., Sugawara S., and Ohmi T. A still-image encoder based on adaptive resolution vector quantization featuring needless calculation elimination architecture. IEEE J. Solid-State Circ. 38 5 (2003) 726-733
5. Vaisey J., and Gersho A. Varibale block-size image coding. Proc. ICASSP'87 (1987) 1051-1054
6. Vaisey J., and Gersho A. Image compression with variable block size segmentation. IEEE Signal Process. 40 8 (1992) 2040-2060
7. Lightstone M., Rose K., and Mitra S.K. Locally optimal codebook design for quadtree-based vector quantization. Proc. IEEE ICASSP '95. Detroit, MI (1995) 2479-2482
8. Sullivan G.J., and Baker R.L. Efficient quadtree coding of images and video. IEEE Trans. Image Process. 3 (1994) 311-327 (no. 3)
9. Wang C.Y., Liao S.J., and Chang L.W. Wavelet image coding using variable blocksize vector quantization with optimal quadtree segmentation. Signal Process.: Image Commun. 15 (2000) 879-890
10. Chang C.-C., Chuang J.-C., and Chung C.-Y. Quadtree-segmented image compression method using vector quantization and cubic B-spline interpolation. Image Sci. J. 52 (2004) 106-116
11. Hu Y.-C., and Chang C.-C. Quadtree-semented image coding schemes using vector quantizagtion and block truncation coding. Opt. Eng. 39 2 (2000) 464-471
12. Suzuki Y., and Miyamoto T. Vector quantization by a self-organizing tree with newly implemented pruning algorithm. The 47th IEEE International Midwest Symposium on Circuit and Systems (2004) 125-128
13. Miyamoto T., Suzuki Y., Saga S., and Maeda J. Vector quantization of images using fractal dimensions. 2005 IEEE Mid-Summer Workshop on Soft Computing in Industrial Application (2005) 214-217
14. Sasazaki K., Ogasawara H., Saga S., Maeda J., and Suzuki Y. Fuzzy vector quantization of images based on local fractal dimensions. IEEE Int. Conf. Fuzzy Syst. (2006) 5992-5997
15. Kim C., Kim R., and Lee S. A fractal vector quantizer for image coding. IEEE Trans. Image Process. 7 11 (1998) 1598-1602
16. M.S. Keane, B.A/M. Svhouten, http://www.cwi.nl/.
17. Barnsely M.F. Fractals Everywhere (1993), Academic Press Professional, Boston
18. S. Novianto, Optimum estimation of local fractal dimension for the segmentation of natural images a dissertation for a Doctor of Engineering, Muroran Institute of Technology, March, 2002.
19. Novianto S., Suzuki Y., and Maeda J. Near optimal estimation of local fractal dimension for image segmentation. Pattern Recognit. Lett. 24 (2003) 365-374
20. Peleg S., Naor J., Hartley R., and Avnir D. Multiple resolution texture analysis and classification. IEEE Trans. Pattern Anal. Machine Intell. 6 4 (1984) 518-523
21. Otsu N., Kurita T., and Sekita I. Pattern Recognit. (1996) (in Japanese)
22. Bellman R.E., and Dreyfus S.E. Dynamic Programming (1962), Princeton University Press, Princeton
23. Karayiannis N.B., and Pai P. Fuzzy vector quantization algorithms and their application in image compression. IEEE Trans. Image Process. 4 9 (1995) 1193-1201
24. Bezdek J.C. Pattern Recognition with Fuzzy Objective Function Algorithms (1981), Plenum, New York
25. Hoppner F., Klawonn F., Kruse R., and Runkler T. Fuzzy Cluster Analysis (1999), John Wiley & Sons Ltd., New York
26. Gata I., and Geva A.B. Unsupervised optimal fuzzy clustering. IEEE Trans. PAMI 11 12 (1989) 773-781
27. Krishnapuram R., and Keller J.M. A possibilistic approach to clustering. IEEE Trans. Fuzzy Syst. 1 2 (1993) 98-110