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Texture feature fusion for high resolution satellite image classification

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3 Author(s)
Yindi Zhao ; LIESMARS, Wuhan Univ., China ; Liangpei Zhang ; Pingxiang Li

Multi-channel Gabor filters (MCGF) and Markov random fields (MRF) have been demonstrated to be quite effective for texture analysis. In this paper, MCGF and MRF features are respectively extracted from input texture images by means of the two above techniques. A MCGF/MRF feature fusion algorithm for texture classification is proposed. The fused MCGF/MRF features achieved by this novel algorithm have much higher discrimination than either the pure features or the combined features without selection, according to the Fisher criterion and classification accuracy. The stability and effectiveness of the proposed algorithm are verified on samples of Brodatz and QuickBird images.

Published in:

Computer Graphics, Imaging and Vision: New Trends, 2005. International Conference on

Date of Conference:

26-29 July 2005