Two-dimensional LMS adaptive filter incorporating a local-mean estimator for image processing

An adaptive scheme is proposed whereby a local-mean estimation substructure is incorporated to overcome the problem of the 2-D least-mean-square (LMS) adaptive filter in dealing with signals having a nonzero mean, especially with abrupt variations (edges), which is a typical feature of practical images. The advantages of this scheme over the direct use of the 2-D LMS are considered. As a direct application, the scheme is used for adaptive cancellation of an artifact disturbance in an image. A method of implementing the local-mean estimation substructure with the edge-preserving property is introduced. Using this local-mean estimator, the scheme is applied to enhancement of images disturbed by wideband noise. All of the application examples illustrate some useful feature of the 2-D LMS adaptive filter in image processing and the improved performance of the scheme