Color image denoising by chromatic edges based vector valued diffusion

In this letter we propose to denoise digital color images via an improved geometric diffusion scheme. By introducing edges detected from all three color channels into the diffusion the proposed scheme avoids color smearing artifacts. Vector valued diffusion is used to control the smoothing and the geometry of color images are taken into consideration. Color edge strength function computed from different planes is introduced and it stops the diffusion spread across chromatic edges. Experimental results indicate that the scheme achieves good denoising with edge preservation when compared to other related schemes.

[1]  V. B. Surya Prasath,et al.  Multispectral image denoising by well-posed anisotropic diffusion scheme with channel coupling , 2010 .

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

[3]  Tom Goldstein,et al.  The Split Bregman Method for L1-Regularized Problems , 2009, SIAM J. Imaging Sci..

[4]  Jean-François Aujol,et al.  Color image decomposition and restoration , 2006, J. Vis. Commun. Image Represent..

[5]  Pierre Kornprobst,et al.  Mathematical problems in image processing - partial differential equations and the calculus of variations , 2010, Applied mathematical sciences.

[6]  Ron Kimmel,et al.  Images as Embedded Maps and Minimal Surfaces: Movies, Color, Texture, and Volumetric Medical Images , 2000, International Journal of Computer Vision.

[7]  Rachid Deriche,et al.  Vector-valued image regularization with PDEs: a common framework for different applications , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Terry Caelli,et al.  Generalized Spatio-Chromatic Diffusion , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Eric Dubois,et al.  Frequency-domain methods for demosaicking of Bayer-sampled color images , 2005, IEEE Signal Processing Letters.

[10]  Jean-Michel Morel,et al.  Geometry and Color in Natural Images , 2002, Journal of Mathematical Imaging and Vision.

[11]  Guillermo Sapiro,et al.  Fast image and video denoising via nonlocal means of similar neighborhoods , 2005, IEEE Signal Processing Letters.

[12]  T. Chan,et al.  Fast dual minimization of the vectorial total variation norm and applications to color image processing , 2008 .

[13]  Ron Kimmel,et al.  Variational Restoration and Edge Detection for Color Images , 2003, Journal of Mathematical Imaging and Vision.

[14]  Guillermo Sapiro,et al.  Color image enhancement via chromaticity diffusion , 2001, IEEE Trans. Image Process..

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

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

[17]  V. B. Surya Prasath.  Weighted laplacian differences based multispectral anisotropic diffusion , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.