2-D adaptive CPWQ filter for image enhancement
Ji-Nan Lin, Rolf Unbehauen · 1993 IEEE International Symposium on Circuits and Systems · 2002
While the least mean square (LMS) adaptive filtering technique is extensively used in 1-D signal processing, its 2-D version achieves only limited success in image processing due to its linear inherence. A 2-D adaptive nonlinear scheme is developed for enhancing images from broadband noise. It is based on a generalization of the conventional concept of optimal linear filtering to the nonlinear case. A new type of adaptive nonlinear filter called the adaptive canonical piecewise-linear (CPWQ) filter is introduced. Simulation examples with an artificial image and a natural image are presented to show the superior performance of the proposed approach in contrast to the 2-D LMS adaptive filter and two other types of nonlinear ones, i.e., the 2-D adaptive Volterra filter and the 2-D adaptive CPWL filter.>