Adaptive filter and morphological operators using binary PSO

Mathematical morphology is a tool for processing shapes in image processing. Adaptively finding the specific morphological filter is an important and challenging task in morphological image processing. In order to model the filter and filtering sequence for morphological operations adaptively, a novel technique based on binary particle swarm optimization (BPSO) is proposed. BPSO is a discrete PSO, where the components values of a particle position vector are either zero or one. The proposed method can be used for numerous types of applications, where the morphological processing is involved including but not limited to image segmentation, noise suppression and patterns recognition etc. The paper illustrates a fair amount of experimental results showing the promising ability of the proposed approach over previously known solutions. In particular, the proposed method is evaluated for noise suppression problem.