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Proceedings Paper

Combined intensity and fractal information for neural classification of remote sensing imagery
Author(s): Kun Shan Chen; C. F. Chen; D. W. Tsay
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Paper Abstract

This paper presents the results of the terrain cover classification from satellite imagery from multispectral SPOT high resolution visible images and ERS-1 C-band SAR image. Fractal image was extracted using, from SAR, a wavelet transform as texture measure. The use of SAR fractal image to combine with SPOT data for terrain cover classification is proved to be effective and efficient, in that for SAR the despeckle process is avoided and thus naturally preserves its texture information. It was found that fractal information significantly improves the discrimination capability of the heterogeneous areas such as in urban regions, while it slightly degrades accuracy for homogeneous areas, such as open water. The overall classification performance is superior to results obtained using intensity image only.

Paper Details

Date Published: 17 November 1995
PDF: 8 pages
Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995); doi: 10.1117/12.226839
Show Author Affiliations
Kun Shan Chen, National Central Univ. (Taiwan)
C. F. Chen, National Central Univ. (Taiwan)
D. W. Tsay, National Central Univ. (Taiwan)


Published in SPIE Proceedings Vol. 2579:
Image and Signal Processing for Remote Sensing II
Jacky Desachy, Editor(s)

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