高光谱遥感光谱相似性度量算法与若干新方法研究

基金项目: 国家自然科学基金资助项目(40401038);测绘遥感信息工程国家重点实验室开放研究基金;中国矿业大学科学基金联合资助项目(D200403)

详细信息

Algorithms for Spectral Similarity Measure in Hyperspectral RS

¹ Dept.of Remote Sensing and Geographical Information Science,China University of Mining and Technology,South Jiefang Road,Xuzhou 221008,China;² Institute of Image Processing and Pattern Recognition,Shanghai Jiaotong University,Huashan Road,Shanghai 200030,China

Funds: 国家自然科学基金资助项目(40401038);测绘遥感信息工程国家重点实验室开放研究基金;中国矿业大学科学基金联合资助项目(D200403)

摘要: 提出了一种新的光谱相似性度量算法分类体系。在归纳算法的基础上,根据不同的度量原理与实现策略,结合应用需求,提出了基于光谱多边形的测度、四值编码、十进制编码、树状变换测度及基于小波变换的测度等新方法,这些方法能够应用于分类、检索等的相似性度量中。
- 高光谱遥感 /
- 相似性度量 /
- 光谱向量
Abstract: Based on the analysis to current algorithms,some new approaches are proposed and experimented.Similarity measure based on spectral polygon considers both albedo and wavelength at the same time so its precision is higher than other methods.Spectral similarity measure based on multi-scale wavelet transformation can combine similarity measure with dimensionality reduction,also have high precision.By experiments it proves that these new approaches can be used to spectral feature-based hyperspectral RS image retrieval effectively.
- hyperspectral remote sensing /
- similarity measure /
- spectral vector