高光谱亚像元定位的线特征探测法

Linear feature detection for hyperspectral subpixel mapping

未考虑地物亚像元级空间结构特征是影响高光谱亚像元定位精度的因素之一。为了有效解决这一问题,本文提出一种基于混合像元线特征探测的亚像元定位算法。首先,通过光谱解混确定含典型线状地物的混合像元。然后,基于完备直线集的最大线性指数方法确定其余含线特征的混合像元,使用模板匹配方法结合像元引力确定含线特征混合像元的亚像元类别。最后,基于线性优化的方法迭代确定剩余混合像元的亚像元类别。通过真实数据及仿真数据的试验,结果表明所提出的方法能有效提高亚像元定位精度。

The ignorance of the spatial structure of subpixel is one of the factors that influence the accuracy of hyperspectral subpixel mapping.In order to effectively solve this problem,a subpixel mapping algorithm is proposed that based on linear feature detection in mixed pixels.Firstly,the mixed pixels of typical linear feature classes are determined by spectral unmixing.Then,based on the maximum linear index method of the complete straight-line set,the linear features of remaining mixed pixels are determined.The template matching method is used in conjunction with the pixel attraction to determine the classes of linear subpixels.Finally,the subpixel categories of the remaining mixed pixels are iteratively determined based on the linear optimization method.The experimental results of real data and simulation data show that the proposed method can effectively improve the precision of subpixel mapping.