A mixture feature selection method for remote sensing image

Xiaochun Cai; Yihua Hu; Xiaohong Tao; Guilan Hu

doi:10.1117/12.657920

4 January 2006 A mixture feature selection method for remote sensing image

Xiaochun Cai, Yihua Hu, Xiaohong Tao, Guilan Hu

Proceedings Volume 5985, International Conference on Space Information Technology; 598530 (2006) https://doi.org/10.1117/12.657920
Event: International Conference on Space information Technology, 2005, Wuhan, China

Abstract

The need for remote sensing image feature selection methods is discussed in this paper. A central problem in image classification and recognition is the redundancy of image features. To cope with many unnecessary and irrelevant features, we propose a mixture method based on principle component analysis (PCA) and rough set theory to alleviate this situation. The main contribution of this paper is to provide the method for remote sensing image classification with higher accuracy comparing to the single rough set theory and PCA method. Finally, some experimental results demonstrate that our proposed method is effective in feature selection for remote sensing image.

Citation Download Citation

Xiaochun Cai, Yihua Hu, Xiaohong Tao, and Guilan Hu "A mixture feature selection method for remote sensing image", Proc. SPIE 5985, International Conference on Space Information Technology, 598530 (4 January 2006); https://doi.org/10.1117/12.657920

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