%0 Journal Article
%T Geometric estimation method of spectral unmixing<br>基于几何估计的光谱解混方法
%A WANG Liguo
%A WANG Qun-Ming
%A LIU Dan-Feng
%A WU Yong-Qing
%A <br>王立国
%A 王群明
%A 刘丹凤
%A 吴永庆
%J 红外与毫米波学报
%D 2013
%I Science Press
%X spectral unmixing in one of the important techniques of hyperspectral data analysis. Full constrained (i.e. non-negative and sum to one constrainted) least squares linear spectral mixture modeling (FCLS-LSMM) is widely used for its conciseness and clarity of physical meaning. Unfortunately, the traditionally iterative processing for solving FCLS-LSMM is of heavy computational burden. Recently developed geometric analysis method of LSMM provided a new way for lowing down the complexity of LSMM solving. The unmixing results, however, are not in line with the FCLS requirements. In this case, a new geometric unmixing method is constructed to completely meet the FCLS requirements. The method is of very low complexity, at the same time, has the capability to obtain the theoretically optimal solution. Experiments show the effective of the proposed method.
%K Hyperspectral
%K Spectral unmixing
%K Fully constrained least squares (FCLS)
%K Linear spectral mixture modeling(LSMM)<br>高光谱
%K 光谱解混
%K 全约束最小二乘(FCLS)
%K 线性光谱混合模型(LSMM)
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=D3B4F771D1A06062008B4D0A2EF05996&aid=575970AF4D203263393FC5A03B436B4B&yid=FF7AA908D58E97FA&vid=9971A5E270697F23&iid=38B194292C032A66&sid=014B591DF029732F&eid=1D0FA33DA02ABACD&journal_id=1001-9014&journal_name=红外与毫米波学报&referenced_num=0&reference_num=0