Edge detection in remote sensing image based on cluster information

Warin Chumsamrong; Punya Thitimajshima

doi:10.1117/12.365887

18 October 1999 Edge detection in remote sensing image based on cluster information

Warin Chumsamrong, Punya Thitimajshima

Proceedings Volume 3808, Applications of Digital Image Processing XXII; (1999) https://doi.org/10.1117/12.365887
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

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.

Citation Download Citation

Warin Chumsamrong and Punya Thitimajshima "Edge detection in remote sensing image based on cluster information", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365887

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