[1] 王满利,田子建,桂伟峰,吴君.基于高斯曲率优化和非下采样剪切波变换的高密度混合噪声去除算法[J].光子学报,2019,48(09):211-226. Wang Man-li,Tian Zi-jian,Gui Wei-feng,Wu Jun.High density mixed noise removal algorithm based on Gaussian curvature optimization and non-subsampled shearlet transform[J].Acta Photonica Sinica,2019,48(09):211-226. (in Chinese) [2] Liu L,Chen L,Chen C L P,et al.Weighted joint sparse representation for removing mixed noise in image[J].IEEE Transactions on Cybernetics,2016,47(3):600-611. [3] Goyal B,Dogra A,Agrawal S,et al.Image denoising review:from classical to state-of-the-art approaches[J].Information Fusion,2020,55(2020):220-244. [4] Griffin L D.Mean,median and mode filtering of images[J].Proceedings of the Royal Society of London.Series A:Mathematical,Physical and Engineering Sciences,2000,456(2004):2995-3004. [5] Vemula M,Bugallo M F,Djuric P M.Performance comparison of Gaussian-based filters using information measures[J].IEEE Signal Processing Letters,2007,14(12):1020-1023. [6] Zhang X,Dai L.Fast bilateral filtering[J].Electronics Letters,2019,55(5):258-260. [7] 王玉灵.基于双边滤波的图像处理算法研究[D].西安:西安电子科技大学,2010. [8] Xie Y,Zhang W,Tao D,et al.Removing turbulence effect via hybrid total variation and deformation-guided kernel regression[J].IEEE Transactions on Image Processing,2016,25(10):4943-4958. [9] Li M,Han C,Wang R,et al.Shrinking gradient descent algorithms for total variation regularized image denoising[J].Computational Optimization and Applications,2017,68(3):643-660. [10] Yang J H,Zhao X L,Mei J J,et al.Total variation and high-order total variation adaptive model for restoring blurred images with cauchy noise[J].Computers & Mathematics with Applications,2019,77(5):1255-1272. [11] Zhang M,Gunturk B.A new image denoising method based on the bilateral filter[A].Acoustics,Speech and Signal Processing[C].USA:IEEE,2008.929-932. [12] Strong D,Chan T.Edge-preserving and scale-dependent properties of total variation regularization[J].Inverse Problems,2003,19(6):S165-S187. [13] Gong Y,Sbalzarini I F.Curvature filters efficiently reduce certain variational energies[J].IEEE Transactions on Image Processing,2017,26(4):1786-1798. [14] 汤成.基于曲率滤波的图像去噪与增强研究[D].浙江:浙江理工大学,2019. [15] Mousavi Z,Lakestani M,Razzaghi M.Combined shearlet shrinkage and total variation minimization for image denoising[J].Iranian Journal of Science and Technology,Transactions A:Science,2018,42(1):31-37. [16] Abazari R,Lakestani M.A hybrid denoising algorithm based on shearlet transform method and Yaroslavsky's filter[J].Multimedia Tools and Applications,2018,77(14):17829-17851. [17] Shahdoosti H R,Khayat O.Image denoising using sparse representation classification and non-subsampled shearlet transform[J].Signal,Image and Video Processing,2016,10(6):1081-1087. [18] Dabov K,Foi A,Katkovnik V,et al.Image denoising by sparse 3-D transform-domain collaborative filtering[J].IEEE Transactions on Image Processing,2007,16(8):2080-2095. [19] Gong Y,Sbalzarini I F.Local weighted Gaussian curvature for image processing[A].Image Processing[C].USA:IEEE,2013.534-538. [20] Miura S,Tsuji H,Kimura T.Randomly valued impulse noise removal using Gaussian curvature of image surface[A].Intelligent Signal Processing and Communication Systems[C].USA:IEEE,2013.291-296. [21] 张承志,冯华君,徐之海,等.图像噪声方差分段估计法[J].浙江大学学报(工学版),2018,52(9):1804-1810. Zhang Cheng-zhi,Feng Hua-jun,Xu Zhi-hai,et al.Piecewise noise variance estimation of images based on wavelet transform[J].Journal of Zhejiang University (Engineering Science),2018,52(9):1804-1810.(in Chinese) [22] Hore A,Ziou D.Image quality metrics:PSNR vs.SSIM[A].International Conference on Pattern Recognition[C].USA:IEEE,2010.2366-2369. |