A generalized adaptive model for nonlinear image restoration

Abstract
An investigation is conducted of noniterative algorithms for the nonlinear image restoration problem. A general, nonlinear image formation model is considered in conjunction with a minimum-mean-square-error (MMSE) restoration approach. For a logarithmic nonlinearity, a filter is analytically derived. The introduction of a combined objective function compensates for the stationarity assumption, incorporating local adaptivity in the nonlinear filter. The nonlinear restoration algorithms introduced are demonstrated through an example.

This publication has 8 references indexed in Scilit: