Title :
Segmenting images corrupted by correlated noise
Author_Institution :
Dept. of Stat., Macquarie Univ., North Ryde, NSW, Australia
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 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
Keywords :
Gaussian noise; correlation methods; image segmentation; piecewise constant techniques; 2D piecewise constant functions; additive Gaussian noise; correlated noise; digital image; image analysis; image segmentation; minimum description length principle; noise corrupted images; nonoverlapping homogeneous regions; Digital images; Gaussian noise; Image analysis; Image segmentation; Indexing; Integrated circuit noise; Labeling; Merging; Proposals; Statistical analysis;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.647751
