A fast and low memory image coding algorithm based on lifting wavelet transform and modified SPIHT

Signal Processing: Image Communication

Volumn 23, Issue 3, 2008, Pages 146-161

  Pan, Hong ^a,b   Siu, Wan Chi ^a   Law, Ngai Fong ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b SOUTHEAST UNIVERSITY   (China)

Author keywords

Lifting wavelet transform; Listless SPIHT; Low bit rate image compression

Indexed keywords

ALGORITHMS; BIT ERROR RATE; HIERARCHICAL SYSTEMS; IMAGE COMPRESSION; IMAGE QUALITY; WAVELET TRANSFORMS;

LIFTING WAVELET TRANSFORM; LOW BIT RATE IMAGE COMPRESSION; LOW MEMORY IMAGE CODING ALGORITHMS; SET PARTITIONING IN HIERARCHICAL TREES (SPIHT);

IMAGE CODING;

EID: 41949136188     PISSN: 09235965     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.image.2008.01.004     Document Type: Article

References (28)

1. Adams M.D., and Kossentini F. Reversible integer-to-integer wavelet transforms for image compression: performance evaluation and analysis. IEEE Trans. Image Process. 9 6 (June 2000) 1010-1024
2. Antonini M., Barlaud M., Mathieu P., and Daubechies I. Image coding using wavelet transform. IEEE Trans. Image Process. 1 (April 1992) 205-220
3. Berghorn W., Boskamp T., Lang M., and Peitgen H.O. Fast variable run-length coding for embedded progressive wavelet-based image compression. IEEE Trans. Image Process. 10 12 (December 2001) 1781-1790
4. Daubechies I., and Sweldens W. Factoring wavelet transforms into lifting steps. J. Fourier Anal. Appl. 4 3 (1998) 267-345
5. Islam A., and Pearlman W.A. An embedded and efficient low-complexity, hierarchical image coder. Visual communication and image processing '99. Proc. SPIE 3653 (January 1999) 294-305
6. JPEG 2000 verification model version 6.0, ISO/IEC JTC 1/SC 29/WG 1, Doc. N 1575, January 2000.
7. N.F. Law, W.C. Siu, Progressive image coding based on visually important features, in: Proceedings of the IEEE International Conference on Image Processing, vol. II, October 1999, pp. 362-366.
8. Law N.F., and Siu W.C. Successive structural analysis using wavelet transform for blocking artifacts suppression. Signal Processing 81 7 (July 2001) 1373-1387
9. Law N.F., and Siu W.C. An efficient computational scheme for the two-dimensional overcomplete wavelet transform. IEEE Trans. Signal Process. 50 11 (November 2002) 2806-2819
10. W.K. Lin, N. Burgess, Listless zerotree coding for color image, in: Proceedings of the 32nd Asilomar Conference on Signal, Systems and Computers, vol. 1, November 1998, pp. 231-235.
11. Mallat S., and Zhong S. Characterization of signals from multiscale edges. IEEE Trans. Pattern Anal. Machine Intell. 14 7 (1992) 710-732
12. Marr D. Vision (1982), Freeman, San Francisco
13. Pearlman W.A., Islam A., Nagaraj N., and Said A. Efficient, low-complexity image coding with a set-partitioning embedded block coder. IEEE Trans. Circuits Systems Video Technol. 14 11 (November 2004) 1219-1235
14. Ran X., and Farvardin N. A perceptually motivated three-component image model-part I: description of the model. IEEE Trans. Image Process. 4 4 (April 1995) 401-415
15. Ran X., and Farvardin N. A perceptually motivated three-component image model-part II: application to image compression. IEEE Trans. Image Process. 4 4 (April 1995) 430-447
16. Said A., and Pearlman W.A. A new, fast and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. Circuits Systems Video Technol. 6 (June 1996) 243-250
17. Shapiro J.M. Embedded image coding using zerotrees of wavelets coefficients. IEEE Trans. Signal Process. 41 (December 1993) 3445-3462
18. J.M. Shapiro, A fast technique for identifying zerotrees in the EZW algorithm, in: Proceedings of the International Conference on Acoustics, Speech and Signal Processing, May 1996, pp. 1455-1458.
19. R.R. Shively, E. Ammicht, P.D. Davis, Generalizing SPIHT: a family of efficient image compression algorithms, in: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2000, vol. 4, June 2000, pp. 2059-2062.
20. M.G. Sun, Q. Liu, K.C. Yi, C.C. Li, R.J. Sclabassi, Fast Internet transmission of physiological signals using the lifting scheme and SPIHT coding algorithm, in: 2002 6th International Conference on Signal Processing, vol. 2, August 2002, pp. 1544-1547.
21. Sweldens W. The lifting scheme: a new philosophy in biorthogonal wavelet constructions. Wavelet applications in signal and image processing III. Proc. SPIE 2569 (1995) 68-79
22. Sweldens W. The lifting scheme: a custom-design construction of biorthogonal wavelets. Appl. Comput. Harmonic Anal. 3 2 (1996) 186-200
23. Sweldens W. The lifting scheme: a construction of second generation wavelets. SIAM J. Math. Anal. 29 2 (1997) 511-546
24. Taubman D. High performance scalable image compression with EBCOT. IEEE Trans. Image Process. 9 (July 2000) 1158-1170
25. Villasenor J.D., Belzer B., and Liao J. Wavelet filter evaluation for image compression. IEEE Trans. Image Process. 4 8 (August 1995) 1053-1060
26. Watson A.B., Yang G.Y., Solomon J.A., and Villasinoi J. Visibility of wavelet quantization noise. IEEE Trans. Image Process. 6 8 (1997) 1164-1175
27. F.W. Wheeler, W.A. Pearlman, SPIHT image compression without lists, in: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2000, vol. 4, June 2000, pp. 2047-2050.
28. Witten I.H., Neal R.M., and Cleary J.G. Arithmetic coding for data compression. Comm. ACM 30 (June 1987) 520-540