Decoupling Noise and Features via Weighted ℓ-Analysis Compressed Sensing

ACM Transactions on Graphics

Volumn 33, Issue 2, 2014, Pages

  Wang, Ruimin ^a   Yang, Zhouwang ^a   Liu, Ligang ^a   Deng, Jiansong ^a   Chen, Falai ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Asymptotic optimality; Denoising; Sharp feature; analysis compressed sensing

Indexed keywords

INVERSE PROBLEMS; LAPLACE TRANSFORMS; OPTIMIZATION; SIGNAL RECONSTRUCTION;

ASYMPTOTIC OPTIMALITY; DE-NOISING; DIFFERENTIAL PROPERTIES; GEOMETRY PROCESSING; LAPLACIAN REGULARIZATIONS; SENSING OPTIMIZATIONS; SHARP FEATURES; UNDERLYING SURFACE;

FEATURE EXTRACTION;

EID: 84899073091     PISSN: 07300301     EISSN: 15577368     Source Type: Journal    
DOI: 10.1145/2557449     Document Type: Article

References (35)

1. H. Avron, A. Sharf, C. Greif, and D. Cohen-Or. 2010. ℓ-sparse reconstruction of sharp point set surfaces. ACM Trans. Graph. 29, 5, 135-154.
2. C. Bajaj and G. Xu. 2003. Anisotropic diffusion of surfaces and functions on surfaces. ACM Trans. Graph. 22, 1, 4-32. (Pubitemid 44769056)
3. Z. Bian and R. Tong. 2011. Feature-preserving mesh denoising based on vertices classification. Comput.-Aided Geom. Des. 28, 1, 50-64.
4. M. Botsch, L. Kobbelt, M. Pauly, P. Alliez, and B. Levy. 2010. Polygon Mesh Processing. AK Peters/CRC Press.
5. S. Boyd and L. Vandenberghe. 2004. Convex Optimization. Cambridge University Press.
6. E. Candes, Y. Eldar, D. Needell, and P. Randall. 2010. Compressed sensing with coherent and redundant dictionaries. Appl. Comput. Harmonic Anal. 31, 1, 59-73.
7. E. Candes and T. Tao. 2005. Decoding by linear programming. IEEE Trans. Inf. Theory 51, 12, 4203-4215. (Pubitemid 41800353)
8. E. Candes and M. Wakin. 2008. An introduction to compressive sampling. IEEE Signal Process. Mag. 25, 2, 21-30.
9. E. Candes, M.Wakin, and S. Boyd. 2008. Enhancing sparsity by reweighted ℓ minimization. J. Fourier Anal. Appl. 14, 5-6, 877-905.
10. U. Clarenz, U. Diewald, and M. Rumpf. 2000. Anisotropic geometric diffusion in surface processing. In Proceedings of the Conference on Visualization (VIS'00). 397-405.
11. E. Cuthill and J.McKee. 1969. Reducing the bandwidth of sparse symmetric matrices. In Proceedings of the 24th ACMNational Conference. 157-172.
12. M. Desbrun, M. Meyer, P. Schroder, and A. Barr. 1999. Implicit fairing of irregular meshes using diffusion and curvature flow. In Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'99). 317-324.
13. D. Donoho. 2006. Compressed sensing. IEEE Trans. Inf. Theory 25, 4, 1289-1306.
14. F. Duguet, F. Durand, and G. Drettakis. 2004. Robust higher-order filtering of points. Tech. rep. RR-5165, INRIA. Basilic/2004/Dug04a/RR-5165.pdf.
15. Y. Eldar and G. Kutyniok. 2012. Compressed Sensing: Theory and Applications. Cambridge University Press.
16. H. Fan, Y. Yu, and Q. Peng. 2010. Robust feature-preservingmesh denoising based on consistent sub-neighborhoods. IEEE Trans. Vis. Comput. Graph. 16, 2, 312-324
17. S. Fleishman, I. Drori, and D. Cohen-Or. 2003. Bilateral mesh denoising. ACM Trans. Graph. 22, 3, 950-953.
18. M. Habbecke and L. Kobbelt. 2012. Linear analysis of nonlinear constraints for interactive geometric modeling. Comput. Graph. Forum 31, 2, 1-10.
19. L. He and S. Schaefer. 2013. Mesh denoising via l0 minimization. ACM Trans. Graph. 32, 4, 64:1-64:8.
20. K. Hildebrandt and K. Polthier. 2004. Anisotropic filtering of nonlinear surface features. Comput. Graph. Forum 23, 3, 391-400.
21. K. Hildebrandt and K. Polthier. 2007. Constraint-based fairing of surface meshes. In Proceedings of the 5th Eurographics Symposium on Geometry Processing (SGP'07). 203-212.
22. T. Jones, F. Durand, andM.Desbrun. 2003. Non-iterative, feature-preserving mesh smoothing. ACM Trans. Graph. 22, 3, 943-949.
23. R. B. Lehoucq, D. C. Sorensen, and C. Yang. 1998. ARPACK Users' Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods, Vol. 6, SIAM.
24. L. Liu, C. Tai, Z. Ji, and G. Wang. 2007. Non-iterative approach for global mesh optimization. Comput.-Aided Des. 39, 9, 772-782. (Pubitemid 47094760)
25. F. J. Massey. 1951. The kolmogorov-smirnov test for goodness of fit. J. Amer. Statist. Assoc. 46, 253, 68-78.
26. A. Nealen, T. Igarashi, O. Sorkine, and M. Alexa. 2006. Laplacian mesh optimization. In Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia (GRAPHITE'06). 381-389. (Pubitemid 47113732)
27. D. C. Sorensen. 1997. Implicitly Restarted Arnoldi/Lanczos Methods for Large Scale Eigenvalue Calculations. Springer.
28. Z. Su, H. Wang, and J. Cao. 2009. Mesh denoising based on differential coordinates. In Proceedings of the IEEE International Conference on Shape Modeling and Applications (SMI'09). 1-6.
29. X. Sun, P. Rosin, R. Martin, and F. Langbein. 2007. Fast and effective feature-preserving mesh denoising. IEEE Trans. Vis. Comput. Graph. 13, 5, 925-938. (Pubitemid 47171112)
30. G. Taubin. 1995. A signal processing approach to fair surface design. In Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'95). 351-358.
31. C. Tomasi and R. Manduchi. 1998. Bilateral filtering for gray and color images. In Proceedings of the 6th International Conference on Computer Vision (ICCV'98). 839-846.
32. G. Wahba. 1990. Spline Models for Observational Data. SIAM, Philadelphia, PA.
33. L. Xu, C. Lu, Y. Xu, and J. Jia. 2011. Image smoothing via L0 gradient minimization. ACM Trans. Graph. 30, 6, 174:1-174:12.
34. H. Yagou, Y. Ohtake, and A. Belyaev. 2002. Mesh smoothing via mean and median filtering applied to face normals. In Proceedings of the Geometric Modeling and Processing - Theory and Applications (GMP'02). 124-131.
35. Y. Zheng, H. Fu, O. K.-C. Au, and C.-L. Tai. 2010. Bilateral normal filtering for mesh denoising. IEEE Trans. Vis. Comput. Graph. 17, 10, 1521-1530.