Wavelet-based level set evolution for classification of textured images

IEEE Transactions on Image Processing

Volumn 12, Issue 12, 2003, Pages 1634-1641

  Aujol, Jean Francois ^a   Aubert, Gilles ^a   Blanc Féraud, Laure ^b  

^a UNIVERSITÉ DE NICE SOPHIA ANTIPOLIS   (France)

^b INRIA   (France)

Author keywords

Active contours; Active regions; Classification; Level set; Multiphase; PDE; Texture; Variational approach; Wavelets

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); FUNCTIONS; MATHEMATICAL MODELS; SET THEORY; STATISTICAL METHODS; TEXTURES; VARIATIONAL TECHNIQUES; WAVELET TRANSFORMS;

ACTIVE CONTOURS; ACTIVE REGIONS; CLASSIFICATION; LEVEL SET; MULTIPHASE; PDE; VARIATIONAL APPROACH; WAVELETS;

IMAGE SEGMENTATION;

EID: 8844268760     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2003.819309     Document Type: Article

References (48)

1. R. Fjortoft, A. Lopes, P. Marthon, and E. Cubero-Castan, "An optimal multiedge detector for sar image segmentation," IEE Trans. Geosci. Remote Sensing, vol. 36, pp. 793-802, May 1998.
2. C. Lemarechal, R. Fjortoft, P. Marthon, E. Cubero-Castan, and A. Lopes, "Sar image segmentation by morphlogical methods," in Proc. SAR image Analysis, Modeling, and Technique III, Sept. 1998.
3. M. Unser, "Texture classification and segmentation using wavelet frames," IEEE Trans. Image Processing, vol. 4, pp. 1549-1560, Nov 1995.
4. M. Berthod, Z. Kato, S. Yu, and J. Zerubia, "Bayesian image classification using markov random fields," Image Vis. Comput., vol. 14, no. 4, pp. 285-293, 1996.
5. C. Bouman and M. Shapiro, "A multiscale random field model for bayesian image segmentation," IEEE Trans. Image Processing, vol. 3, pp. 162-177, 1994.
6. S. Lakshmanan and H Derin, "Simultaneous parameter estimation and segmentation of gibbs random fields using simulated annealing," IEEE Trans. Pattern Anal Machine Intell., vol. 11, pp 799-813, Aug. 1989.
7. B Manjunath and R. Chellappa, "Unsupervised texture segmentation using markov random fields models," IEEE Trans. Pattern Anal Machine Intell., vol. 13, pp. 478-482, May 1991.
8. Z. Kato, "Modélization Markoviennes Multirésolutions en Vision par Ordinateur. Application à la Segmentation d'Images Spot," Ph D. dissertation (in French and English), Université de Nice Sophia Antipolis, 1994.
9. G. Aubert and P. Kornprobst, Mathematical Problems in Image Processing, ser. Applied Mathematical Sciences. New York: Springer-Verlag, 2002, vol. 147.
10. C. Samson, L. Blanc-Feraud, G. Aubert, and J. Zerubia, "A level set method for image classification," Int. J.Comput. Vis., vol. 40, no. 3, pp 187-197, 2000.
11. _, "A variational model for image classification and restoration," IEEE Trans. Pattern Anal Machine Intell., vol. 22, pp. 460-472, May 2000.
12. N. Paragios and R. Deriche, "Geodesic active regions and level set methods for supervised texture segmentation," Int. J. Comput. Vis., vol. 46, no. 3, 2002.
13. G. Unal, A. Yezzi, and H. Krim, Information-Theoretic Active Polygons for Unsupervised Texture Segmentation, 2002.
14. H.-K. Zhao, T. Chan, B. Merriman, and S. Osher, "A variational level set approach to multiphase motion," J. Comput. Phys., vol. 127, pp. 179-195, July 1996.
15. V. Caselles, F. Catte, T. Coll, and F. Dibos, "A geometric model for active contours," Numerische Mathematik, vol. 66, pp. 1-31, 1993.
16. M. Sussman, P. Smereka, and S. Osher, "A level set approach for computing solutions to incompressible two-phase flow," J. Comput. Phys., vol. 114, pp. 146-159, 1994.
17. S. Osher and R. Fedkiw, "Level set methods: An overview and some recent results," J. Comput. Phys., vol. 169, pp. 463-502, 2001.
18. S. C. Zhu and A. Yuille, "Region competition: Unifying snakes, region growing, and bayes/mdl for multi-band image segmentation," IEEE Trans. Pattern Anal. Machine Intell., vol. 18, no. 9, 1996.
19. T. Chan and L. Vese, "Active contours without edges," IEEE Trans Image Processing, vol. 10, pp. 266-77, Feb. 2001.
20. L. Vese and T. Chan, "A multiphase level set framework for image segmentation using the mumford and shah model," Int. J. Comput. Vis., vol 50, no. 3, pp. 271-293, 2002.
21. C. Samson, L. Blanc-Féraud, G. Aubert, and J. Zerubia, "Two variational models for multispectral image classification," in Proc. 3rd Int. Workshop on EMMCVPR, Sophia Antipolis, France, Sept. 2001.
22. Handbook of Pattern Recognition and Image Processing, T. Young and K. Fu, Eds., Norman C. Einspruch, 1986.
23. B. Julesz, "Texton gradients: The texton theory revisited," Biol Cybern., vol. 54, pp. 245-251, 1986.
24. J. Malik and P. Perona, "Preattentive texture discrimination with early vision mecanisms," J. Opt. Suc. Amer. A. vol. 7, no. 5, pp. 923-932, May 1990.
25. G. Koepfler, C. Lopez, and J. Morel, "A multiscale algorithm for image segmentation by variational method," SIAM J. Numer. Anal., vol. 31, no. 1, pp. 282-299, Feb. 1994.
26. D. Dunn and W. Higgins, "Optimal gabor filters for texture segmentation," IEEE Trans. Image Processing, vol. 4, pp. 947-964, July 1995.
27. S. Grigorescu, N. Petkov, and P. Kruizinga, "Comparison of textures features based on gabor filters," IEEE Trans. Image Processing, vol. 11, pp. 1160-1167, Oct. 2002.
28. H. Choi and R. Baraniuk, "Multiscale image segmentation using wavelet-domain hidden markov models," IEEE Trans. Image Processing, vol. 10, pp. 1309-1321, Sept. 2001.
29. C. Bouman, "Multiple resolution segmentation of textured images," IEEE Trans. Pattern Anal. Machine Intell., vol 13, pp. 99-113, July 1995.
30. N. Fatemi-Ghomi, P Palmer, and M. Petrou, "Performance evaluation of texture segmentation algorithms based on wavelets," in Proc. Workshop on Performance Characteristics of Vision Algorithms, Cambridge, U.K., Apr. 1996.
31. G. V. de Wouwer, P. Scheunders, and D. V. Dyck, "Statistical texture characterization from discrete wavelet representation," IEEE Trans. Image Processing, vol. 8, pp. 592-598, Apr. 1999.
32. P. Scheunders, S. Liven, G. V. de Wouwer, P. Vautrot, and D. V. Dyck, "Wavelet-based texture analysis," Int. J. Comput. Sci. Inform. Manage., Dec. 1997.
33. T. Chang and C. Kuo, "Texture analysis and classification with tree-structured wavelet transform," IEEE Trans. Image Processing, vol. 2, pp. 429-441, Oct. 1993.
34. S. Mallat, "A theory for multiresolutionsignal decomposition: The wavelet representation," IEEE Trans. Pattern Anal. Machine Intell., vol. 11, pp. 674-693, July 1989.
35. M. Crouse, R. Nowak, and R. Baraniuk, "Wavelet-based statistical signal processing using hidden Markov models," IEEE Trans. Signal Processing, vol. 46, pp. 886-902, Apr. 1998.
36. J. Liu and P. Moulin, "Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients," IEEE Trans. Image Processing, vol. 10, pp. 1647-1658, Nov. 2001.
37. J. Chen and A. Kundu, "Rotation and gray scale transform invariant texture identification using wavelet decomposition and hidden markov model," IEEE Trans. Pattern Anal. Machine Intell., vol. 16, pp. 208-214, Feb. 1994.
38. D. Leporini and J. Pesquet, "Bayesian wavelet denoising: Besov priors and nongaussian noises," Signal Process., vol. 81, pp. 55-67, 2001.
39. H. Choi and R. Baraniuk, "Multiple basis wavelet denoising using Besov projections," in Proc. IEEE Int. Conf. Image Processing, vol. 1, 1999, pp. 595-9.
40. _, "Information-theoretic interpretation of besov spaces," Proc. SPIE. Aug. 2000.
41. Y. Meyer, "Oscillating patterns in image processing and in some nonlinear evoltion equations," in The Fifteenth Dean Jacquelines B. Lewis Memorial Lectures, Mar. 2001.
42. I. Daubechies, Ten Lectures on Wavelets. Philadelphia. PA: SIAM, 1992.
43. N. K. Paragios, "Geodesic Active Regions and Level set Methods. Contributions and Applications in Artificial Vision," Ph.D. dissertation, Univ. Nice Sophia Antipolis, 2000.
44. S. Mallat, A Wavelet Tour of Signal Processing. New York: Academic. 1998.
45. 2(i)," Trans. Amer. Math. Soc., vol. 315, no. 1, pp. 69-87, Sept. 1989
46. A Laine and J. Fan, "Texture classification by wavelet packet signatures," IEEE Trans. Pattern Anal. Machine Intell., vol. 11, pp. 1186-1190, 1993.
47. G. Aubert and J. Aujol, "Signed Distance Functions and Viscosity Solutions of Discontinuous Hamilton-Jacobi Equations,", ENRIA Res. Rep. 4507, 2002.
48. D. Mumford and J. Shah, "Boundary detection by minimizing functionals," in Proc. IEEE Conf. Computer Vison and Pattern Recognition, San Francisco, CA, 1985.