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Proceedings Paper

Remote sensing image classification method using neural network based on generalized image
Author(s): Tianqiang Peng; Bicheng Li
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Paper Abstract

Conventional classification methods cannot recognize the phenomena of "same spectrum with different land matters" so as to degrade classification accuracy. To solve the problem, this paper proposes a new classification method using neural network based on generalized image, where the space information of the image are exploited. Firstly, we combine the original image with its smoothed image to form a binary set called as a "generalized image," which contains the space information of the original image. Secondly, we make use of artificial neural networks (ANN) to train and classify the "generalized image." Finally, we get the classification result of the original image from that of the "generalized image." Experiment results show that the new method is very efficient, and the classification accuracy is improved largely compared with the classic ANN method.

Paper Details

Date Published: 11 June 2003
PDF: 5 pages
Proc. SPIE 4898, Image Processing and Pattern Recognition in Remote Sensing, (11 June 2003); doi: 10.1117/12.467878
Show Author Affiliations
Tianqiang Peng, Information Engineering Univ. (China)
Bicheng Li, Information Engineering Univ. (China)


Published in SPIE Proceedings Vol. 4898:
Image Processing and Pattern Recognition in Remote Sensing
Stephen G. Ungar; Shiyi Mao; Yoshifumi Yasuoka, Editor(s)

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