Multichannel filters for image processing

Konstantinos N. Plataniotis, Dimitri Androutsos, Anastasios N. Venetsanopoulos

Abstract: New filters for multichannel image processing are introduced and analysed. The proposed methodology constitutes a unifying and powerful framework for multichannel signal processing. The new filters use fuzzy membership functions based on different distance measures among the image vectors to adapt to local data in the image. Fuzzy aggregators are utilized to determine the weights in the proposed filter structure. The special case of colour image processing is studied as an important example of multichannel signal processing. Simulation results indicate that the new filters are computationally attractive and have excellent performance.