Hyperspectral RS image classification based on fractal and rough set

Yunjun Zhan; Guangdao Hu; Yanbin Yuan

doi:10.1117/12.774577

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10 November 2007 Hyperspectral RS image classification based on fractal and rough set

Yunjun Zhan, Guangdao Hu, Yanbin Yuan

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Proceedings Volume 6795, Second International Conference on Space Information Technology; 67954F (2007) https://doi.org/10.1117/12.774577
Event: Second International Conference on Spatial Information Technology, 2007, Wuhan, China

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.

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Yunjun Zhan, Guangdao Hu, and Yanbin Yuan "Hyperspectral RS image classification based on fractal and rough set", Proc. SPIE 6795, Second International Conference on Space Information Technology, 67954F (10 November 2007); https://doi.org/10.1117/12.774577

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