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Coupled anisotropic diffusion for image selective smoothing
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DOI：10.1016/j.sigpro.2005.09.019.png)
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In this paper, we present a novel approach for image selective smoothing by the evolution of two coupled nonlinear partial differential equations. The diffusion coefficient in de-noising equation controls the speed of diffusion, and is determined by the edge-strength function. In the previous works, the edge-strength function depends on isotropic smoothing of the image, which results in failing to preserve corners and junctions, and may also result in failing to resolve small features that are closely grouped together. The presented approach obtains the edge-strength function by solving a nonlinear diffusion equation governed by the norm of the image gradient. This edge-strength function is then introduced into a well-studied anisotropic diffusion model to yield a regularized diffusion coefficient for image smoothing. An explicit numerical scheme is employed to efficiently solve these two coupled equations. Compared with the existing methods, the presented approach has the advantages of more detail preservation and implementational simplicity. Experimental results on the synthesis and real images confirm the validity of the proposed approach. (C) 2005 Elsevier B.V. All rights reserved.
Keyword:
computer vision
anisotropic diffusion
image smoothing
partial differential equation
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