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Noise will occur in the image acquisition. These noises deteriorate the image quality, blur the image and even submerge and change the features, which will bring difficulties to image analysis and recognition. Therefore, filtering methods are usually used to eliminate these noises. Median filtering is quite effective in image denoising. This paper proposes an improved median filtering algorithm. This algorithm uses the characteristic of the motion of the filtering window and the data relevance, which will reduce the time of image de-noising. Based on the median filtering algorithm, it improves the method to seek the median value, gives the optimal weight coefficient to the pixel point according to the relevance between the signal pixel and the central pixel in the filtering window, and improves the de-noising effect accuracy. This improved median filtering algorithm can preserve the image details and achieve better de-noising effect. The simulation experiment proves that the algorithm of this paper can reduce the time the median filtering requires and enhances the signal to noise ratio of the image so that it can improve the efficiency while guarantee the de-noising effect, which is of great practical significance to eliminate noises.

An Improved Median Filtering Image De-noising Algorithm