Share Email Print

Proceedings Paper

Hyperspectral RS image classification based on fractal and rough set
Author(s): Yunjun Zhan; Guangdao Hu; Yanbin Yuan
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The multisperctral trait of hyperspectral RS is a new technology for RS image recognition and classification, on the other hand, it is difficult to image processing owing to trait of data redundancy. This paper propose new method for hyperspectral RS image classification. In order to reduce dimension, utilizing the hyperspectral RS's refined spectral characteristic, we extract every pixel's spectral characteristic curve, and compute the fractal dimension of the curve. By studying the relation between object and spectral characteristic curve and fractal dimension, the paper indicates that the dilation fractal dimension is equal or close to same target wherever it locates, and different from different target. Then based on every pixel's fractal dimension that interval is from 1 to 2, we stretch linearly the interval from 0 to 255, and construct a new gray image. Lastly, we apply the approximate classing of rough set theory class to the new image, the result of classing is namely the result of hyperspectral RS image classification.

Paper Details

Date Published: 10 November 2007
PDF: 6 pages
Proc. SPIE 6795, Second International Conference on Space Information Technology, 67954F (10 November 2007); doi: 10.1117/12.774577
Show Author Affiliations
Yunjun Zhan, China Univ. of Geoscience (China)
Wuhan Univ. of Technology (China)
Guangdao Hu, China Univ. of Geoscience (China)
Yanbin Yuan, Wuhan Univ. of Technology (China)

Published in SPIE Proceedings Vol. 6795:
Second International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Jiaolong Wei, Editor(s)

© SPIE. Terms of Use
Back to Top