L - lters for noise suppression inimagesC

Several adaptive LMS L-lters, both constrained and unconstrained ones, are developed for noise suppression in images and being compared in this paper. First, the location-invariant LMS L-lter for a nonconstant signal corrupted by zero-mean additive white noise is derived. It is demonstrated that the location-invariant LMS L-lter can be described in terms of the generalized linearly constrained adaptive processing structure proposed by Griiths and Jim. Subsequently, the normalized and the signed error LMS L-lters are studied. A modiied LMS L-lter with nonhomogeneous step-sizes is also proposed in order to accelerate the rate of convergence of the adaptive L-lter. Finally, a signal-dependent adaptive lter structure is developed to allow a separate treatment of the pixels that are close to the edges from the pixels that belong to homogeneous image regions.