A Variational Approach to Removing Multiplicative Noise
暂无分享,去创建一个
[1] Dominic Welsh,et al. Probability: An Introduction , 1986 .
[2] Antonin Chambolle,et al. Image Decomposition into a Bounded Variation Component and an Oscillating Component , 2005, Journal of Mathematical Imaging and Vision.
[3] Jean-Pierre Véran,et al. Restoration of SAR Images Using Recovery of Discontinuities and Non-linear Optimization , 1997, EMMCVPR.
[4] J. Ball. A version of the fundamental theorem for young measures , 1989 .
[5] H. Brezis. Opérateurs maximaux monotones et semi-groupes de contractions dans les espaces de Hilbert , 1973 .
[6] Gjlles Aubert,et al. Mathematical problems in image processing , 2001 .
[7] W. D. Evans,et al. PARTIAL DIFFERENTIAL EQUATIONS , 1941 .
[8] Tony F. Chan,et al. Image processing and analysis , 2005 .
[9] Yves Meyer,et al. Oscillating Patterns in Image Processing and Nonlinear Evolution Equations: The Fifteenth Dean Jacqueline B. Lewis Memorial Lectures , 2001 .
[10] R. E. Edwards,et al. Functional Analysis: Theory and Applications , 1965 .
[11] M Tur,et al. When is speckle noise multiplicative? , 1982, Applied optics.
[12] Jerome Bruniquel,et al. Analysis and enhancement of multitemporal SAR data , 1994, Remote Sensing.
[13] Jean-Michel Morel,et al. A Review of Image Denoising Algorithms, with a New One , 2005, Multiscale Model. Simul..
[14] G. Anzellotti,et al. The Euler equation for functionals with linear growth , 1985 .
[15] E. Giusti. Minimal surfaces and functions of bounded variation , 1977 .
[16] R. Temam. Navier-Stokes Equations , 1977 .
[17] Rachid Deriche,et al. Image Sequence Analysis via Partial Differential Equations , 1999, Journal of Mathematical Imaging and Vision.
[18] V. Caselles,et al. Parabolic Quasilinear Equations Min-imizing Linear Growth Functionals , 2004 .
[19] Eitan Tadmor,et al. A Multiscale Image Representation Using Hierarchical (BV, L2 ) Decompositions , 2004, Multiscale Model. Simul..
[20] Thomas R. Crimmins. Geometric Filter For Reducing Speckle , 1986 .
[21] David C. Munson,et al. A signal processing view of strip-mapping synthetic aperture radar , 1989, IEEE Trans. Acoust. Speech Signal Process..
[22] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[23] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[24] M. Nikolova. An Algorithm for Total Variation Minimization and Applications , 2004 .
[25] Pierre Hellier,et al. A Modified Total Variation Denoising Method in the Context of 3D Ultrasound Images , 2004, MICCAI.
[26] Stanley Osher,et al. Multiplicative Denoising and Deblurring: Theory and Algorithms , 2003 .
[27] I. Johnstone,et al. Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .
[28] S. Osher,et al. Geometric Level Set Methods in Imaging, Vision, and Graphics , 2011, Springer New York.
[29] L. Ambrosio,et al. Functions of Bounded Variation and Free Discontinuity Problems , 2000 .
[30] A. Chambolle. An algorithm for Mean Curvature Motion , 2004 .
[31] L. Evans. Measure theory and fine properties of functions , 1992 .
[32] P. Townsend. Principles and Applications of Imaging Radar: Manual of Remote Sensing , 2000 .
[33] J. Goodman. Statistical Properties of Laser Speckle Patterns , 1963 .
[34] Henri Maitre,et al. Smoothing speckled synthetic aperture radar images by using maximum homgeneous region filters , 1992 .