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Proceedings Paper

Edge detection in remote sensing image based on cluster information
Author(s): Warin Chumsamrong; Punya Thitimajshima
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Paper Abstract

In this paper, a multispectral image edge detection algorithm is proposed based on the idea that uses global multispectral information to guide local gradient computation. The image is first segmented into a small number of clusters through a clustering algorithm. According to these clusters, a set of linear projection vectors are generated. For a given image, if n clusters are found, there are n(n-1)/2 possible projection vectors. Edge detection is performed by calculating gradient magnitudes separately on each channel. An appropriate projection vector is chosen for each pixel to maximize gradient magnitude. In this way, edges are treated as transitions from one cluster to another. The algorithm has been tested on JERS-1/OPS images, and the experimental results demonstrate its potential usefulness.

Paper Details

Date Published: 18 October 1999
PDF: 4 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365887
Show Author Affiliations
Warin Chumsamrong, King Mongkut's Institute of Technology Ladkrabang (Thailand)
Punya Thitimajshima, King Mongkut's Institute of Technology Ladkrabang (Thailand)

Published in SPIE Proceedings Vol. 3808:
Applications of Digital Image Processing XXII
Andrew G. Tescher, Editor(s)

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