Nonlinear Diffusion Filters without Parameters for Image Segmentation

Nonlinear diffusion filtering seeks to improve images qualitatively by removing noise while preserving details and even enhancing edges. However, well known implementations are sensitive to parameters which are necessarily tuned to sharpen a narrow range of edge slopes. In this work, we have selected a nonlinear diffusion filter without control parameters. It has been guided searching the optimum balance between time performance and resulting quality suitable for automatic segmentation tasks. Using a semi-implicit numerical scheme, we have determined the relationship between the slope range to sharpen and the diffusion time. It has also been selected the diffusivity with optimum performances. Several diffusion filters have been applied to noisy computed tomography images and evaluated for their suitability to the medical image segmentation. Experimental results show that our proposal of filter performs quite well in relation to others.

[1]  Stephen L. Keeling,et al.  Nonlinear anisotropic diffusion filters for wide range edge sharpening , 2000, Medical Imaging: Image Processing.

[2]  Michel Barlaud,et al.  Variational approach for edge-preserving regularization using coupled PDEs , 1998, IEEE Trans. Image Process..

[3]  R. Stollberger,et al.  Nonlinear anisotropic diffusion filtering for multiscale edge enhancement , 2002 .

[4]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[5]  Satyanad Kichenassamy,et al.  The Perona-Malik Paradox , 1997, SIAM J. Appl. Math..

[6]  Gabriel Asensio,et al.  Analytical Approximations for Nonlinear Diffusion Time in Multiscale Edge Enhancement , 2009, VISAPP.

[7]  Leo Joskowicz,et al.  An iterative Bayesian approach for nearly automatic liver segmentation: algorithm and validation , 2008, International Journal of Computer Assisted Radiology and Surgery.

[8]  P. Lions,et al.  Image selective smoothing and edge detection by nonlinear diffusion. II , 1992 .

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

[10]  Max A. Viergever,et al.  Efficient and reliable schemes for nonlinear diffusion filtering , 1998, IEEE Trans. Image Process..

[11]  Joachim Weickert,et al.  A Review of Nonlinear Diffusion Filtering , 1997, Scale-Space.

[12]  Jean-Michel Morel,et al.  A Review of Image Denoising Algorithms, with a New One , 2005, Multiscale Model. Simul..

[13]  Joachim Weickert,et al.  A semidiscrete nonlinear scale-space theory and its relation to the Perona - Malik paradox , 1996, TFCV.