In this paper, a novel approach to the problem of impulsive noise removal in color digital images is presented. The described switching filter is based on the rank weighted, cumulated pixel dissimilarity measures, which are used for the detection of image samples contaminated by impulsive noise process. The introduced adaptive design enables the filter to tune its parameters to the amount of impulsive noise corrupting the image. The comparison with existing denoising schemes shows that the new technique more efficiently removes the impulses introduced by the noise process, while better preserving image details. An important feature of the new filter is its low computational complexity, which allows for its application in real-time applications.
In the paper a fast technique of impulsive noise removal in color images is described. The proposed method is assigning to pixels of the filtering window the sum of the distances to their k nearest neighbors. The difference between the trimmed sum assigned to the central pixel and to the pixel minimizing the cumulated distances is treated as a measure of pixel's distortion caused by the impulsive noise process. If the difference exceeds a global threshold value, then the central pixel of the processing window is replaced by the mean of the pixels from the window, which were found to be not corrupted, otherwise the central pixel is retained. The new filtering design is able to effectively suppress impulsive noise, while preserving fine image details. The performance comparison shows that the proposed filtering design yields significantly better denoising results than the most efficient filters developed for the impulsive noise suppression in color images.
Abstract. In this paper a novel approach to the problem of speckle noise suppression in ultrasound images is presented. The described method is a modification of the bilateral denoising scheme and is based on the concept of local neighborhood exploration. The proposed filtering design, like the bilateral filter, takes into account the similarity of pixels intensities together with their spatial distance, and the filter output is calculated as a weighted average of the pixels belonging to the filtering window. The weights assigned to the pixels are determined by minimum connection costs of digital paths joining the central pixel of the filtering window and its neighbors. The comparison with existing denoising schemes shows that the new technique yields significantly better results in case of ultrasound images contaminated by multiplicative noise.
Abstract. In this paper a new method of multiplicative noise reduction in ultrasound images is proposed. The novel technique is a modification of the bilateral denosing scheme, which takes into account the similarity of pixels and their spatial distance. The filter output is calculated as a weighted average of the pixels which are in the neighborhood relation with the center of the filtering window, and the weights are functions of the minimal connection costs between surounding pixels. Experimental results show that the proposed method yields significantly better results than the other techniques in case of ultrasound images contaminated by medium and strong multiplicative noise disturbances.
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