Issue No. 05 - May (1998 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.682178
<p><b>Abstract</b>—Image segmentation is fundamental to many image analysis problems. It aims to partition a digital image into a set of nonoverlapping homogeneous regions. The main contribution of this paper is the development of a new segmentation procedure which is designed to segment images corrupted by <it>correlated</it> noise. This new segmentation procedure is based on Rissanen's minimum description length (MDL) principle and consists of two components: i) an MDL-based criterion in which the "best" segmentation is defined as its minimizer and ii) a merging algorithm which attempts to locate this minimizer. The performance of this procedure is illustrated via a simulation study, with promising results.</p>
Correlated noise, image segmentation, merging algorithm, minimum description length.
T. C. Lee, "Segmenting Images Corrupted by Correlated Noise," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 481-492, 1998.