基于多字典稀疏表示的遥感图像亚像元映射

本文提出了一种基于多字典稀疏表示的亚像元映射算法,利用已知的同类型高空间分辨率地物分布图像,构建能够更好反映不同类别地物空间分布模式的多个字典,将待分类亚像元用每一类字典稀疏表示,并依据重构误差最小化原则以及光谱失真程度约束条件来划分亚像元的地物类别.模拟与真实数据上的实验结果表明,本文算法能有效应对地物空间分布模式的多样性,具有更高的亚像元映射精度和更好的算法鲁棒性.

Subpixel Land Cover Mapping Based on Multi-dictionary Sparse Representation for Remote Sensing Images

This paper proposes a subpixel land cover mapping method based on multi-dictionary sparse representation.In this method, some known high spatial resolution land cover maps are used to formulate different dictionaries that represent distribution modes of different land cover classes, the unclassified subpixels are represented by each dictionary, and they are also classified according to the principle of reconstruction-error minimization and spectral distortion constraint.Experimental results both on artificial and real images show that the method deals with the diversity between different distribution modes of different land cover classes effectively, and achieves higher subpixel mapping accuracy and robustness than the other related methods.