Switching median filter with signal dependent thresholds designed by using genetic algorithm

In this paper, we propose a new switching median filter with signal dependent thresholds designed by a genetic algorithm (GA). The switching median filter detects noise-corrupted pixels based on a threshold. Then it restores only the detected pixels. The present switching median filter deals with the random-valued impulse noises, whose distribution is ideally assumed as a uniform distribution. In the present method, the switching median filter, which has two kinds of the thresholds, is introduced. One is switching thresholds to detect the noise, and the other is selecting thresholds to choose the suitable switching threshold. As the suitable selecting threshold, a variance of signals is used. Then all of the switching and selecting thresholds of the proposed switching median filter are automatically optimized by using GA. To optimize the thresholds with GA, distribution distance between the assumed and the detected noises is employed as a fitness function. The validity and effectiveness of the proposed method is verified by some experiments.