基于丰度划分的高光谱遥感图像解混
A Hyperspectral Imagery Unmixing Method Based on Abundance Division
余淞淞1
作者信息
- 1. 同济大学电子信息与工程学院，上海 201804
- 折叠
摘要
高光谱遥感成像技术能够获取目标区域丰富的光谱信息和空间信息。混合像元现象在遥感图像中普遍存在，处理遥感图像解混问题是提高地物识别精度的前提。由于端元光谱可变性的存在，传统的基于单一单元光谱的线性解混方法解混精度难以达到应用要求。对多端元光谱策略进行分析，并给出一种基于丰度划分的高光谱解混算法，对实际光谱数据进行试验并取得较好效果。
Abstract
Hyperspectral remote sensing imagery provides rich spectral information and space information about the place of interest. Mixed pixels happen in spectral images frequently, which reduce the classification accuracy of ground truth. Due to spectral variability, early spectral unmixing methods using one pixel as endmember ectral unmixing can't provide enough performance for applications. Pays more attention to the multiple endmember spectral analysis, and proposes an unmixing method based on abundance division. Experiments on real hyper-spectal images show high performance.
关键词
高光谱/混合像元/光谱解混/丰度划分Key words
Hyperspectral/Mixed Pixel/Spectral Unmixing/Abundance Division引用本文复制引用
出版年
2015
NETL
NSTL
维普
万方数据