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基于拉格朗日分解算法的SAR图像混合像元分解
引用本文:余先川,初晓凤,曹恒智,胡丹.基于拉格朗日分解算法的SAR图像混合像元分解[J].地球物理学进展,2010,25(1):316-323.
作者姓名:余先川  初晓凤  曹恒智  胡丹
作者单位:北京师范大学,信息科学与技术学院,北京,100875
基金项目:北京市自然科学基金,国家自然科学基金,国家863计划,教育部新世纪优秀人才支持计划项目联合资助 
摘    要:为解决与光学遥感图像不同的合成孔径雷达(SAR)图像中存在大量混合像元的问题,本文提出了一种基于拉格朗日分解算法的SAR图像混合像元分解的方法,结合相关内容中具体定理的证明,文中给出拉格朗日分解算法用于SAR图像混合像元分解的系统的求解方法.用人工模拟SAR图像和ENVISAT SAR图像进行实验,结果表明拉格朗日分解算法的混合像元分解结果明显优于非约束类神经网络(文中实验以BP神经网络为例)的分解结果.

关 键 词:合成孔径雷达  混合像元分解  神经网络  拉格朗日约束  空间数据挖掘  盲源分离
收稿时间:2009-07-10
修稿时间:2009-11-21

Decomposition of SAR image mixed pixels based on lagrangian constrained neural network
YU Xian-chuan,CHU Xiao-feng,CAO Heng-zhi,HU Dan.Decomposition of SAR image mixed pixels based on lagrangian constrained neural network[J].Progress in Geophysics,2010,25(1):316-323.
Authors:YU Xian-chuan  CHU Xiao-feng  CAO Heng-zhi  HU Dan
Institution:(College of Information Science and Technology, Beijing Normal University, Beijing 100875, China)
Abstract: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).
Keywords:syntheticapertureradar(SAR)  decompositionofmixedpixels  neuralnetwork  lagrangianconstrainted  spatialdatamining  blindsourceseparation
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