In this paper, we present a novel approach for image selective smoothing by the evolution of two paired nonlinear
partial differential equations. The distribution coefficient in de-noising equation controls the speed of distribution, 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 proposed approach obtains the edge-strength function by solving a
nonlinear distribution equation governed by the norm of the image gradient. This edge-strength function is then introduced
into a well-studied anisotropic distribution model to yield a regularized distribution coefficient for image smoothing. An explicit
numerical scheme is employed to efficiently solve these two paired equations. Compared with the existing methods, the
proposed approach has the advantages of more detailed preservation and implementational simplicity. Experimental results
on the synthesis and real images confirm the validity of the proposed approach.
Top