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PAMI
1998

Segmenting Images Corrupted by Correlated Noise

13 years 4 months ago
Segmenting Images Corrupted by Correlated Noise
—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 correlated 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.
Thomas C. M. Lee
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 1998
Where PAMI
Authors Thomas C. M. Lee
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