http://www.gissky.net- GIS空间站

传统非负矩阵分解算法的目标函数具有大量的局部极小,在进行高光谱图像的光谱解混时,受初始值的影响很大.为解决该问题,作者通过在目标函数中引入丰度分离性和平滑性的约束条件,提出一种基于有约束非负矩阵分解的混合像元分解方法.同时该算法能够满足混合像元分解问题所要求的丰度值非负以及和为一的约束.模拟和实际数据实验结果表明,所提出的算法能够很好地克服局部极小的问题,从而得到更优的解.同时该算法表现出了较强的抗噪声能力,并且能够适用于无纯像元数据的混合像元分解. 更多还原

【Abstract】 Because of the local minima in the objective function,the traditional Nonnegative Matrix Factorization(NMF) algorithm is sensitive to the initial value when being applied to hyperspectral unmixing.In order to solve the problem,a new approach based on constrained NMF was proposed for decomposition of mixed pixels by introducing constraints of abundance separation and smoothness into the objective function of NMF.The algorithm can also satisfy the abundance nonnegative and sum-to-one constraints,w... 更多还原