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A new approach to edge-preserving smoothing of digital images designed for an effective elimination of the image noise within digital images what is an essential step in applications like edge detection or image segmentation is introduced. This paper introduces a new approach to edge-preserving smoothing of digital images. It is designed for an effective elimination of the image noise within digital images what is an essential step in applications like edge detection or image segmentation. The approach presented here tries to overcome some of the disadvantages of existing smoothing filters and is conceived as an extension of the edge-preserving Maximum Homogeneity Neighbour Filter. The algorithm cleans up the image noise in the homogeneous areas, but preserves all image structures like edges or corners. It is shown that the new filter algorithm combines the advantageous features of different types of filters. The algorithm is not only applicable to grayscale images, but can be extended to multi-channel data, like color images too. The performance of the algorithm is achieved by a more complex and differentiating treatment of the image data compared to conventional concepts.
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