Adaptive image denoising in scale-space using the wavelet transform

Brazilian Symposium of Computer Graphic and Image Processing

Volumn 2001-January, Issue , 2001, Pages 172-178

  Jung, C R ^a   Scharcanski, J ^b  

^a FEDERAL UNIVERSITY OF RIO GRANDE DO SUL   (Brazil)

^b UNIVERSIDADE DO VALE DO RIO DOS SINOS   (Brazil)

Author keywords

Denoising; Edge detection; Multiresolution analysis; Wavelet shrinkage

Indexed keywords

COMPUTER GRAPHICS; EDGE DETECTION; IMAGE PROCESSING; INVERSE PROBLEMS; MULTIRESOLUTION ANALYSIS; SHRINKAGE; WAVELET DECOMPOSITION; WAVELET TRANSFORMS;

DE-NOISING; GEOMETRIC CONSTRAINT; INVERSE WAVELET TRANSFORMS; MODIFIED COEFFICIENT; MULTI RESOLUTION DECOMPOSITION; REDUNDANT WAVELET TRANSFORM; SHRINKAGE FUNCTIONS; WAVELET SHRINKAGE;

IMAGE DENOISING;

EID: 28844450203     PISSN: 15301834     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIBGRAPI.2001.963052     Document Type: Conference Paper

References (15)

1. S. G. Mallat and W. L. Hwang, "Singularity detection and processing with wavelets", IEEE Transactions on Information Theory, vol. 38, no. 2, pp. 617-643, 1992.
2. R. A. Carmona, "Extrema reconstructions and spline smoothing: Variations on an algorithm of Mallat and Zhong", Wavelets and Statistics - Lecture Notes in Statistics, vol. 103, pp. 83-94, 1995.
3. Y. Xu, J. B. Weaver, D. M. Healy, and J. Lu, "Wavelet transform domain filters: A spatially selective noise filtration technique", IEEE Transactions on Image Processing, vol. 3, no. 6, pp. 747-758, 1994.
4. M. Malfait and D. Roose, "Wavelet based image denoising using a Markov Random Field a priori model", IEEE Transactions on Image Processing, vol. 6, no. 4, pp. 549-565, 1997.
5. E. P. Simoncelli and E. Adelson, "Noise removal via bayesian wavelet coring", in IEEE International Conference on Image Processing, (Lausanne, Switzerland), pp. 279-382, September 1996.
6. S. G. Chang and M. Vetterli, "Spatial adaptive wavelet thresholding for image denoising", in 7997 International Conference on Image Processing (ICIP97), pp. 374-377, 1997.
7. S. G. Chang, B. Yu, and M. Vetterli, "Spatially adaptive wavelet thresholding with context modeling for image denoising", IEEE Transactions on Image Processing, vol. 9, pp. 1522-1531, September 2000.
8. M. K. Mihcak, I. Kozintsev, K. Ramchandram, and P. Moulin, "Low-complexity image denoising based on statistical modeling of wavelet coefficients", IEEE Signal Processing Letters, vol. 6, pp. 300-303, December 1999.
9. V. Strela, J. Portilla, and E. P. Simoncelli, "Image denoising via a local gaussian scale mixture model in the wavelet domain", in SPIE 45th Annual Meeting, (San Diego, CA), August 2000.
10. A. Pizurica, W. Philips, I. Lemahieu, and M. Acheroy, "Image de-noising in the wavelet domain using prior spatial constraints", in Seventh International Conference on Image Processing and its Applications, (Manchester, England), pp. 216-219, IEE, July 1999.
11. S. G. Mallat and S. Zhong, "Characterization of signals from multiscale edges", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 7, pp. 710-732, 1992.
12. S. G. Mallat, "A theory for multiresolution signal decomposition: The wavelet representation", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, no. 7, pp. 674-693, 1989.
13. D. L. Donoho, "Nonlinear wavelet methods for recovery of signals, densities and spectra from indirect and noisy data", in Proc Symp Appl Math (I. Daubechies, ed.), (Providence, RI), 1993.
14. D. L. Donoho, "Wavelet shrinkage and w.v. d.: A 10-minute tour", Progress in Wavelet Analysis and Applications, 1993.
15. D. L. Donoho and I. M. Johnstone, "Ideal spatial adaptation by wavelet shrinkage", Biometrika, vol. 81, pp. 425-455, 1994.