%0 Journal Article
%T Decomposition of SAR image mixed pixels based on lagrangian constrained neural network<br>基于拉格朗日分解算法的SAR图像混合像元分解
%A 余先川
%A 初晓凤
%A 曹恒智
%A 胡丹
%J 地球物理学进展
%D 2010
%I 
%X 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).
%K syntheticapertureradar(SAR)
%K decompositionofmixedpixels
%K neuralnetwork
%K lagrangianconstrainted
%K spatialdatamining
%K blindsourceseparation<br>合成孔径雷达
%K 混合像元分解
%K 神经网络
%K 拉格朗日约束
%K 空间数据挖掘
%K 盲源分离
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=1E44AE713D8A6DE0&jid=65CE641AB2DEAAF8B2D39ECB6B6B6C80&aid=0627D0FA73287C49787944FC4D774B22&yid=140ECF96957D60B2&vid=C5154311167311FE&iid=CA4FD0336C81A37A&sid=EC34D52BE81085CE&eid=892C6E385D640C1E&journal_id=1004-2903&journal_name=地球物理学进展&referenced_num=0&reference_num=20