A new artificial immune network classifier for SAR image

Ruochen Liu; Manchun Niu

doi:10.1117/12.832898

30 October 2009 A new artificial immune network classifier for SAR image

Ruochen Liu, Manchun Niu

Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 74960W (2009) https://doi.org/10.1117/12.832898
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Inspired by the idiotypic network theory, a new artificial immune network classifier for SAR image is proposed in this paper. In the proposed algorithm, only one B-cell instead of many B-cells is used to denote a class so as to reduce the scale of network as well as avoid the suppression operation between B-cells; moreover, a new affinity function based on the correct rate is proposed to realize antigen priority based the evaluation strategy. The proposed algorithm has been extensively compared with Fuzzy C-means (FCM), Multiple-Valued Immune Network algorithm (MVIN), and Clonal Selection Algorithm for classifier (CSA) over two SAR images. The result of experiment indicates the superiority of the algorithm over FCM, MVIN and CSA on classification accuracy and robustness.

Citation Download Citation

Ruochen Liu and Manchun Niu "A new artificial immune network classifier for SAR image", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74960W (30 October 2009); https://doi.org/10.1117/12.832898

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