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《Progress in Geophysics》 2010-01
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Decomposition of SAR image mixed pixels based on lagrangian constrained neural network

YU Xian-chuan,CHU Xiao-feng,CAO Heng-zhi,HU Dan (College of In formation Science and Technology,Beijing Normal University,Beijing 100875,China)  
For resolving the problem of mixed pixels that the Synthetic Aperture Radar (SAR) image has which is different from optical remote sensing image, we apply the Lagrangian constrained neural network to decomposition of SAR image mixed pixels.Combining the demonstration of specific theorem in relevant content, we propose a systemic solving method which uses Lagrange constrained neural network decompose the mixed pixels of the SAR image.We make experiments on artificial simulated SAR images and ENVISAT SAR images.Experimental results show that the Lagrangian constrained neural network can get significantly more precise results than other neural network which does not contain restrictive conditions, (such as the BP neural network).
【Fund】: 北京市自然科学基金(4062020);; 国家自然科学基金(40672195 40372129);; 国家863计划(2007AA12Z156);; 教育部新世纪优秀人才支持计划项目联合资助
【CateGory Index】: TN957.52
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