Multi-source remote sensing image fusion classification based on DS evidence theory

Chunping Liu; Xiaohu Ma; Zhiming Cui

doi:10.1117/12.751283

14 November 2007 Multi-source remote sensing image fusion classification based on DS evidence theory

Chunping Liu, Xiaohu Ma, Zhiming Cui

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67903C (2007) https://doi.org/10.1117/12.751283
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

A new adaptive remote sensing image fusion classification based on the Dempster-Shafer theory of evidence is presented. This method uses a limited number of prototypes as items of evidence, which is automatically generated by modified Fuzzy Kohonen Clustering Network (FKCN). The class fuzzy membership of each prototype is also determined using reference pattern set. For each input vector a basic probability assignment (BPA) function are computed based on these distances and on the degree of membership of prototypes to each class. And lastly this evidence is combined using Dempster's rule. This proposed method can be implemented in a modified FKCN with specific architecture consisting of one input layer, a prototype layer, a BPA layer, a combination and output layer, and decision layer. The experimental results show that the excellent performance of classification as compared to existing FKCN and basic DS fusion techniques.

Citation Download Citation

Chunping Liu, Xiaohu Ma, and Zhiming Cui "Multi-source remote sensing image fusion classification based on DS evidence theory", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67903C (14 November 2007); https://doi.org/10.1117/12.751283

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