Segmenting images corrupted by correlated noise

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 non-overlapping homogeneous regions. This paper describes a new segmentation procedure which is designed to segment images corrupted by correlated noise. This procedure is based on R...

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Bibliographic Details
Published in:Proceedings of International Conference on Image Processing Vol. 1; pp. 247 - 250 vol.1
Main Author: Lee, T.C.M.
Format: Conference Proceeding
Language:English
Published: IEEE 1997
Subjects:
Digital images
Gaussian noise
Image analysis
Image segmentation
Indexing
Integrated circuit noise
Labeling
Merging
Proposals
Statistical analysis
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Summary: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 describes a new segmentation procedure which is designed to segment images corrupted by correlated noise. This procedure is based on Rissanen's (1989) minimum description length principle.
ISBN:0818681837
9780818681837
DOI:10.1109/ICIP.1997.647751