Abstract

Image segmentation is fundamental to many image analysis problems. It aims to partition a digital image into a set of non--overlapping homogeneous regions. This paper briefly describes a new segmentation procedure which is designed to segment images corrupted by correlated noise. This procedure is based on Rissanen 's minimum description length principle. 1 Introduction One popular approach to segmenting an image based on greyvalue is to approximate the image by a 2D piecewise smooth function and define the segmentation by the discontinuity points of the 2D function. In this paper images that can be well modelled by 2D piecewise constant functions (PCFs) corrupted by additive Gaussian noise will receive primary attention. The main contribution here is the proposal of a new segmentation procedure which is designed to segment such images when the noise is correlated. The proposed segmentation procedure is based on Rissanen's minimum description length (MDL) principle [4] and consists ...

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