A variational model with hybrid Hyper-Laplacian priors for Retinex

[1]  Yiqiu Dong,et al.  Cauchy Noise Removal by Nonconvex ADMM with Convergence Guarantees , 2017, Journal of Scientific Computing.

[2]  Yong Chen,et al.  Group sparsity based regularization model for remote sensing image stripe noise removal , 2017, Neurocomputing.

[3]  Ting-Zhu Huang,et al.  Truncated l1-2 Models for Sparse Recovery and Rank Minimization , 2017, SIAM J. Imaging Sci..

[4]  Tingzhu Huang,et al.  A non-convex tensor rank approximation for tensor completion , 2017 .

[5]  Sheng Zhong,et al.  Hyper-Laplacian Regularized Unidirectional Low-Rank Tensor Recovery for Multispectral Image Denoising , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Xiao-Ping Zhang,et al.  A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Chuanjiang He,et al.  A Variational Model with Barrier Functionals for Retinex , 2015, SIAM J. Imaging Sci..

[8]  Xiaoqun Zhang,et al.  Retinex by Higher Order Total Variation L1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L^{1}$$\end{document} Decomp , 2015, Journal of Mathematical Imaging and Vision.

[9]  Lei Zhang,et al.  Discriminative learning of iteration-wise priors for blind deconvolution , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[10]  Stanley Osher,et al.  Non-Local Retinex - A Unifying Framework and Beyond , 2015, SIAM J. Imaging Sci..

[11]  Tieyong Zeng,et al.  Retinex image enhancement via a learned dictionary , 2015 .

[12]  M. Ng,et al.  A nonlocal total variation model for image decomposition: Illumination and reflectance , 2014 .

[13]  Michael K. Ng,et al.  A New Convex Optimization Model for Multiplicative Noise and Blur Removal , 2014, SIAM J. Imaging Sci..

[14]  David Zhang,et al.  A Generalized Iterated Shrinkage Algorithm for Non-convex Sparse Coding , 2013, 2013 IEEE International Conference on Computer Vision.

[15]  Hai-Miao Hu,et al.  Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images , 2013, IEEE Transactions on Image Processing.

[16]  R. Chan,et al.  Nonstationary iterated thresholding algorithms for image deblurring , 2013 .

[17]  Alan C. Bovik,et al.  Making a “Completely Blind” Image Quality Analyzer , 2013, IEEE Signal Processing Letters.

[18]  Michael K. Ng,et al.  Deblurring and Sparse Unmixing for Hyperspectral Images , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[19]  S. Osher,et al.  A TV Bregman iterative model of Retinex theory , 2012 .

[20]  Liangpei Zhang,et al.  A Perceptually Inspired Variational Method for the Uneven Intensity Correction of Remote Sensing Images , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[21]  Aichi Chien,et al.  An L1-based variational model for Retinex theory and its application to medical images , 2011, CVPR 2011.

[22]  Stephen P. Boyd,et al.  Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers , 2011, Found. Trends Mach. Learn..

[23]  Michael K. Ng,et al.  A Total Variation Model for Retinex , 2011, SIAM J. Imaging Sci..

[24]  Jean-Michel Morel,et al.  A PDE Formalization of Retinex Theory , 2010, IEEE Transactions on Image Processing.

[25]  Michael K. Ng,et al.  Solving Constrained Total-variation Image Restoration and Reconstruction Problems via Alternating Direction Methods , 2010, SIAM J. Sci. Comput..

[26]  Hédy Attouch,et al.  Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Lojasiewicz Inequality , 2008, Math. Oper. Res..

[27]  Rob Fergus,et al.  Fast Image Deconvolution using Hyper-Laplacian Priors , 2009, NIPS.

[28]  Azeddine Beghdadi,et al.  Natural Rendering of Color Image based on Retinex , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[29]  Jean-Michel Morel,et al.  Fast implementation of color constancy algorithms , 2009, Electronic Imaging.

[30]  Frédo Durand,et al.  Image and depth from a conventional camera with a coded aperture , 2007, ACM Trans. Graph..

[31]  Alessandro Rizzi,et al.  Mathematical definition and analysis of the retinex algorithm. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[32]  Michael Elad,et al.  A Variational Framework for Retinex , 2002, IS&T/SPIE Electronic Imaging.

[33]  Farhan A. Baqai,et al.  Analysis and extensions of the Frankle-McCann Retinex algorithm , 2004, J. Electronic Imaging.

[34]  Dimitri P. Bertsekas,et al.  Convex Analysis and Optimization , 2003 .

[35]  David Mumford,et al.  Statistics of natural images and models , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[36]  Edward H. Adelson,et al.  Noise removal via Bayesian wavelet coring , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[37]  Marc Teboulle,et al.  Hidden convexity in some nonconvex quadratically constrained quadratic programming , 1996, Math. Program..

[38]  David J. Field,et al.  What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[39]  D. Ruderman.  The statistics of natural images , 1994 .

[40]  E H Land,et al.  An alternative technique for the computation of the designator in the retinex theory of color vision. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Andrew Blake,et al.  Boundary conditions for lightness computation in Mondrian World , 1985, Comput. Vis. Graph. Image Process..

[42]  E H Land,et al.  Recent advances in retinex theory and some implications for cortical computations: color vision and the natural image. , 1983, Proceedings of the National Academy of Sciences of the United States of America.

[43]  Berthold K. P. Horn,et al.  Determining lightness from an image , 1974, Comput. Graph. Image Process..

[44]  E. Land,et al.  Lightness and retinex theory. , 1971, Journal of the Optical Society of America.

[45]  E H Land,et al.  COLOR VISION AND THE NATURAL IMAGE PART II. , 1959, Proceedings of the National Academy of Sciences of the United States of America.