Wavelet-based image processing

International Journal of Phytoremediation

Volumn 85, Issue 4, 2006, Pages 439-458

  Walker, James S ^a  

^a UNIVERSITY OF WISCONSIN EAU CLAIRE   (United States)

Author keywords

Image Compression; Image Processing; Wavelets

Indexed keywords

EID: 84055164620     PISSN: 15226514     EISSN: 15497879     Source Type: Journal    
DOI: 10.1080/00036810500358874     Document Type: Article

References (33)

1. Ash, RB. 1990. Information Theory, New York: Dover.
2. Burt, PA, and Adelson, EH. 1983. The Laplacian pyramid as a compact image code. IEEE Transactions on Communications, 31: 532–540.
3. Bell, TC, Cleary, JG, and Witten, IH. 1990. Text Compression, Englewood Cliffs, NJ: Prentice-Hall.
4. Davis, GM. 1998. A Wavelet-Based Analysis of Fractal Image Compression. IEEE Trans. on Image Proc., 7: 213–45.
5. Davis, GM, and Nosratinia, A. 1999. Wavelet-based image coding: An overview. Applied and Computational Control, Signals and Circuits, 1: 25–48.
6. Field, DJ. 1999. Wavelets, vision and the statistics of natural scenes. Philosophical Transactions of the Royal Society, 357: 2527–2542.
7. Field, DJ, and Brady, N. 1997. Wavelets, blur and the sources of variability in the amplitude spectra of natural scenes. Vision Research, 37: 3367–83.
8. Hendricks, B, Choi, H, and Baraniuk, RQ. 1999. “ Analysis of texture segmentation using wavelet-domain hidden Markov trees ”. In Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA: SPIE Press.
9. Jähne, B. 2002. Digital Image Processing, 5th Edn, Berlin: Springer.
10. Li, J, and Lei, S. 1999. An embedded still image coder with rate distortion optimization. IEEE Trans. on Image Processing, 8: 913–24.
11. Mallat, S. 1989. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11: 674–693.
12. Mallat, S. 1999. A Wavelet Tour of Signal Processing, 2nd Edn, New York: Academic Press.
13. Marr, D. 1982. Vision, San Francisco, CA: W.H. Freeman.
14. Mumford, D, and Shah, J. 1989. “ Boundary detection by minimizing functionals I ”. In Image Understanding, New York: Ablex Press.
15. Nguyen, TQ, and Koilpillai, RD. 1996. Theory and design of arbitrary-length cosine-modulated filter banks and wavelets satisfying perfect reconstruction. IEEE Trans. on Signal Processing, 44: 473–83.
16. Pennebaker, WB, and Mitchell, JL. 1992. JPEG Still Image Compression, London: Chapman and Hall.
17. Queiroz, RL, and Tran, TD. 2001. “ Lapped transforms for image compression ”. In The Transform and Data Compression Handbook, Edited by: Rao, KR, and Yip, PC. Boca Raton, FL: CRC/Chapman Hall. Chap. 5
18. Rao, KR, and Yip, P. 1990. Discrete Cosine Transform: Algorithms, Advantages, Applications, Boston, MA: Academic Press.
19. Pearlman, WA, and Said, A. 1996. A new, fast, efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. on Circuits and Systems for Video Tech., 6: 243–50.
20. Shapiro, JM. 1993. Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing, 41: 3445–62.
21. Oraintara, S. 2000. “ Regular linear phase perfect reconstruction filter banks for image compression ”. Boston University. Ph.D. dissertation
22. Strang, G, and Nguyen, TQ. 1996. Wavelets and Filter Banks, Boston, MA: Wellesley-Cambridge Press.
23. Taubman, DS, and Marcellin, MW. 2002. JPEG2000: Image Compression Fundamentals, Standards and Practice, Boston, MA: Kluwer.
24. Walker, JS. 1999. A Primer on Wavelets and their Scientific Applications, Boca Raton, FL: CRC/Chapman Hall.
25. Walker, JS, and Nguyen, TQ. 2001. “ Wavelet-based image compression ”. In The Transform and Data Compression Handbook, Edited by: Rao, KR, and Yip, PC. Boca Raton, FL: CRC/Chapman Hall. Chapter 6
26. Walker, JS, and Nguyen, TQ. 2000. Adaptive scanning methods for wavelet difference reduction in lossy image compression. IEEE International Conference on Image Processing, Vancouver, Sept. 2000, 3: 182–85.
27. Walker, JS. 2003. “ New methods in wavelet-based image denoising ”. In Progress in Analysis: Proceedings of the 3rd International ISAAC Congress, Edited by: Begehr, HGW, Gilbert, RP, and Wong, MW. New Jersey: World Scientific. (Eds)
28. Walker, JS. 2002. Tree-Adapted Wavelet Shrinkage.
29. Walker, JS. 2002. Combined image compressor and denoiser based on tree-adapted wavelet shrinkage. Optical Engineering, 41: 1520–27.
30. Walnut, DF. 2002. An Introduction to Wavelet Analysis, Boston, MA: Birkhauser.
31. Wandell, BA. 1995. Foundations of Vision, Sunderland, MA: Sinauer Associates Inc.
32. Watson, AB. 1987. Efficiency of a model human image code. Journal of the Optical Society of America, 4: 2401–17.
33. Chen, YJ, Oraintara, S, and Amaratunga, K. 2005. Dyadic-based factorizations for regular paraunitary filter banks and M-band orthogonal wavelets with strutural vanishing moments. 53: 193–207. Submitted to IEEE Transactions on Signal Processing