Perona-Malik Model with a New Diffusion Coefficient for Image Denoising

This paper presents a new diffusion coefficient which is based on second order derivative and local entropy information for image denoising. In the proposed model, a second order derivative term is introduced, which reduces the staircasing effect and preserves edge in a processed image. The local entropy information can preserve texture. The Perona–Malik model with a new diffusion coefficient improves the denoised effects, and prevents edges from being over-smoothed. Comparative experiments show that the proposed model obtains more satisfied results than the other two existing models.

[1]  Michael Elad,et al.  On the origin of the bilateral filter and ways to improve it , 2002, IEEE Trans. Image Process..

[2]  Ruomei Yan,et al.  Natural image denoising using evolved local adaptive filters , 2014, Signal Process..

[3]  Wenqi Ren,et al.  Anisotropic second and fourth order diffusion models based on Convolutional Virtual Electric Field for image denoising , 2013, Comput. Math. Appl..

[4]  Jing Hu,et al.  Non-local means algorithm with adaptive patch size and bandwidth , 2013 .

[5]  Hyenkyun Woo,et al.  Non-convex hybrid total variation for image denoising , 2013, J. Vis. Commun. Image Represent..

[6]  Ling Shao,et al.  Nonlocal Hierarchical Dictionary Learning Using Wavelets for Image Denoising , 2013, IEEE Transactions on Image Processing.

[7]  J. K. Mandal,et al.  Wavelet based Denoising of Medical Images Using Sub-band Adaptive Thresholding through Genetic Algorithm , 2013 .

[8]  Martin Vetterli,et al.  Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..

[9]  Wenyuan Xu,et al.  Behavioral analysis of anisotropic diffusion in image processing , 1996, IEEE Trans. Image Process..

[10]  Lihong Huang,et al.  A new nonlocal total variation regularization algorithm for image denoising , 2014, Math. Comput. Simul..

[11]  Xiangyang Wang,et al.  Image denoising using bilateral filter and Gaussian scale mixtures in shiftable complex directional pyramid domain , 2011, Comput. Electr. Eng..

[12]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[13]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[15]  Sung-Jin Song,et al.  Non-local means theory based Perona-Malik model for image denosing , 2013, Neurocomputing.

[16]  L. Shao,et al.  From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms , 2014, IEEE Transactions on Cybernetics.

[17]  Richard G. Baraniuk,et al.  Anisotropic Nonlocal Means Denoising , 2011, ArXiv.