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21 August 2013 Camouflaged target separation by spectral-polarimetric imagery fusion with shearlet transform and clustering segmentation
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Proceedings Volume 8908, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Sensors and Applications; 89081G (2013) https://doi.org/10.1117/12.2033944
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China
Abstract
Camouflaged targets detection in complex background is a challenging problem. Spectral-polarimetric imaging can offers spectral information and polarization information from the objects in the scene. Fusion of the spectral and polarization information in the images will result in better camouflaged target identification and recognition. In this paper a novel spectral-polarimetric image fusion algorithm based on Shearlet transform is proposed. Firstly, every polarimetric image in each wave band is decomposed into images of low frequency components and high frequency components by Shearlet transform. Then, the fused low frequency approximate coefficients are obtained with weighted average method, and the fused high frequency coefficients are obtained with area-based feature selection method, so features and details from different spectral-polarimetric images are fused successfully. After that, the kernel fuzzy c-means clustering algorithm is used for camouflaged object separation from its background. Experimental results have shown that better identification performance was achieved.
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Pu-cheng Zhou and Cun-chao Liu "Camouflaged target separation by spectral-polarimetric imagery fusion with shearlet transform and clustering segmentation", Proc. SPIE 8908, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Sensors and Applications, 89081G (21 August 2013); https://doi.org/10.1117/12.2033944
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