基于Top-Hat变换的高光谱吸收特征增强方法

对地物高光谱进行特征分析是高光谱影像用于目标识别和地物分类的基础.基于数学形态学的Top-Hat变换提出了一种光谱吸收峰增强算法.该方法在增强吸收峰的同时还保持了吸收谱带的波形特征.从美国地质调查局USGS光谱数据库选取的11条不同矿物的反射光谱曲线,对其吸收峰增强曲线和原始光谱曲线进行了K-means聚类分析.结果表明:吸收峰增强曲线的聚类结果在波形上和地质背景上都优于原始光谱曲线;且将吸收峰增强曲线的聚类的结果用矿物光谱的ASTER影像采样光谱曲线显示时,能总结出各组矿物的ASTER光谱典型特征.说明吸收峰增强曲线很好地增强了矿物光谱的吸收特征,提高了高光谱的可分性,同时还能为基于多光谱数据的遥感信息提取提供参考,是十分有用的高光谱分析方法.

A novel hyperspectra absorption enhancing method based on morphological top-hat transformation

Hyperspectral characteristics analysis of ground features is the basis for applications of high-resolution imaging technology to ground target identification and ground features classification. Based on morphological multi-scale Top-Hat transformation, a novel spectral absorption enhancing algorithms was put forward, which enhanced spectral absorption features while maintaining shape features of the absorption peak bands. Eleven reflectance spectra of different mineral groups were chosen from the mineral spectral library of the United States Geological Survey (USGS), and we used a K-means clustering analysis on both the absorption-enhanced spectra and the original reflectance spectra. Results showed that, firstly, clustering groups of the absorption-enhanced spectra (AES) had better similarity within the same clustering group, and greater difference between different groups, furthermore, they were more consistent with the geological background of these minerals compared with clustering result of the original spectra (OS). Secondly, while all the original spectra were re-sampled to their ASTER spectra and the AES clustering result was displayed in the form of ASTER spectra of the minerals, we could easily describe both the representative spectral feature of each clustering group, and the typical spectral differences between every two groups. These fully demonstrate that the absorption-enhanced spectra have enhanced absorption features of the mineral spectra, and improved the separability of hyper-spectra. Accordingly, feature analysis based on absorption enhanced spectra can be used as reference for information extracting based on multi-spectral remote sensing image data, and it is a very useful method of hyperspectral analysis.