Genetic-based fuzzy hybrid multichannel filters for color image restoration

On the design of multichannel filters, especially in color image restoratio n, it is not easy to simultaneously achieve three objectives: noise attenua tion, chromaticity retention, and edges or details preservation. In this pa per we propose a new class of multichannel filters, called genetic-based fu zzy hybrid multichannel (GFHM) filters, to reach these three objectives sim ultaneously. The design of GFHM filters is mainly based on human concept (h euristic rules) and genetic algorithms. Because the human concept can be re adily and efficiently expressed by fuzzy implicative rules, GFHM filters ca n take the useful characteristics of filtering behavior of three filters: a vector median, a vector directional, and an identity filter. Since genetic algorithms possess the global-searching capability for an optimal solution , they are able to effectively optimize GFHM filters to improve the filteri ng performance. In color image restoration applications, extensive simulati on results illustrate that GFHM filters not only achieve these three object ives but also possess the robust and the adaptive capability; moreover, the se simulation results also demonstrate that the performance of GFHM filters outperforms that of other proposed filtering techniques. (C) 2000 Elsevier Science B.V. All rights reserved.