Buades A, Coll B, Morel J M. A non-local algorithm for image denoising. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005. 60-65
[2]
Easley G R, Labate D, Colonna F. Shearlet based total variation for denoising. IEEE Transactions on Image Processing, 2009, 16(2): 260-268
Huang D A, Kang L W, Wang Y C, Lin C W. Self-learning based image decomposition with applications to single image denoising. IEEE Transactions on Multimedia, 2014, 16(1): 83-93
[5]
Xue Qian, Yang Cheng-Yi, Wang Hua-Xiang. Alternating direction method for salt-and-pepper denoising. Acta Automatica Sinica, 2013, 39(12): 2071-2076(薛倩, 杨程屹, 王化祥. 去除椒盐噪声的交替方向法. 自动化学报, 2013, 39(12): 2071-2076)
[6]
Mahmoudi M, Sapiro G. Fast image and video denoising via non-local means of similar neighborhoods. IEEE Signal Processing Letters, 2005, 12(12): 839-842
[7]
Yan R M, Shao L, Cvetkovic S D, Klijn J. Improved nonlocal means based on pre-classification and invariant block matching. Journal of Display Technology, 2012, 8(4): 212-218
[8]
Zhang X D, Feng X C, Wang W W. Two-direction nonlocal model for image denoising. IEEE Transactions on Image Processing, 2013, 22(1): 408-412
[9]
Hao Hong-Xia, Liu Fang, Jiao Li-Cheng, Wu Jie. A non-local means algorithm for image denoising using structure adaptive window. Journal of Xi'an Jiaotong University, 2013, 47(12): 71-76(郝红侠, 刘芳, 焦李成, 武杰. 采用结构自适应窗的非局部均值图像去噪算法. 西安交通大学学报, 2013, 47(12): 71-76)
[10]
Elad M, Aharon M. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image Processing, 2006, 15(12): 3736-3745
[11]
Dabov K, Foi A, Katkovnik V, Egiazarian K. Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Transactions on Image Processing, 2007, 16(8): 2080-2095
[12]
Muresan D D, Parks T W. Adaptive principal components and image denoising. In: Proceedings of the 2003 International Conference on Image Processing. Barcelona, Spain: IEEE, 2003. 101-104
[13]
Zhang L, Dong W S, Zhang D, Shi G M. Two-stage image denoisng by principal component analysis with local pixel grouping. Pattern Recognition, 2010, 43(4): 1531-1549
[14]
He Y M, Gan T, Chen W F, Wang H J. Adaptive denoising by singular value decomposition. IEEE Signal Processing Letters, 2011, 18(4): 215-219
[15]
Dabov K, Foi A, Katkovnik V, Egiazarian K. BM3D image denoising with shape-adaptive principal component analysis. In: Proceedings of the 2009 Workshop on Signal Processing with Adaptive Sparse Structured Representations. Saint-Malo, France: IEEE, 2009. 1-6
[16]
Wang H C, Ahuja N. Rank-R approximation of tensors using image-as-matrix representation. In: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005. 346-353
[17]
Ding C, Ye J P. Two-dimensional singular value decomposition (2DSVD) for 2D Maps and images. In: Proceedings of the 2005 SIAM International Conference on Data Mining. Newpot Beach, USA: SIAM, 2005. 32-43
[18]
Maj J B, Royackers L, Moonen M, Wouters J. SVD-based optimal filtering for noise reduction in dual microphone hearing aids: a real reduction time implementation and perceptual evaluation. IEEE Transactions on Biomedical Engineering, 2005, 52(9): 1563-1573
[19]
Buades A, Coll B, Morel J M. A review of image denoising algorithms, with a new one. SIAM Journal on Multiscale Modeling and Simulation, 2005, 4(2): 490-530
[20]
Donoho D L, Johnstone I M. Ideal spatial adaptation via wavelet shrinkage. Biometrica, 1994, 81: 425-455
[21]
Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, 13(4): 600-612
