Texture Classification Based on Mapping Complex Directionlet

Bai Jing; Jia Jian-hua; Jiao Li-cheng

doi:10.3724/SP.J.1146.2008.00513

Volume 31 Issue 6

Jun. 2009

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Article Navigation > Journal of Electronics & Information Technology > 2009 > 31(6): 1332-1336

Bai Jing, Jia Jian-hua, Jiao Li-cheng. Texture Classification Based on Mapping Complex Directionlet[J]. Journal of Electronics & Information Technology, 2009, 31(6): 1332-1336. doi: 10.3724/SP.J.1146.2008.00513

Citation:

Bai Jing, Jia Jian-hua, Jiao Li-cheng. Texture Classification Based on Mapping Complex Directionlet[J]. Journal of Electronics & Information Technology, 2009, 31(6): 1332-1336. doi: 10.3724/SP.J.1146.2008.00513

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Texture Classification Based on Mapping Complex Directionlet

doi: 10.3724/SP.J.1146.2008.00513 cstr: 32379.14.SP.J.1146.2008.00513

Received Date: 2008-04-28
Rev Recd Date: 2009-01-06
Publish Date: 2009-06-19

Abstract

Abstract

Directionlet transform can capture the image singularity due to possessing the multi-direction anisotropic basis functions. A texture classification algorithm based on the Mapping complex Directionlet Transform (M-DT) is proposed, which provides better directionality and approximate shift invariance. By space mapping for the texture image, then complex Directionlet transform is applied to the mapped image, and the multiscale subband coefficient energy feature is used for texture classification. The experiments using texture images from Brodatz and real SAR images indicate the proposed method outperforms wavelets and Multiscale Geometric Analysis (MGA) approaches, the potential application to image analysis by Directionlet is thus proved.

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References(1)

References

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