摘要
根据光谱特征拟合算法在实际应用中存在的问题,介绍一种改进光谱特征拟合算法,该算法综合常规的特征拟合处理和地物光谱吸收特征参量约束为一体,能更细致地进行高光谱数据地物信息提取。实验基于不同空间分辨率和信噪比的高光谱数据,编程实现改进光谱特征拟合算法对实验区的白云母、方解石、绿泥石等蚀变矿物信息提取,与常规光谱特征拟合和光谱角制图处理结果的比较分析发现改进算法在矿物混淆区分、信息提取精细度上均得到提高,有较强的实用性。
Spectral feature fitting（SFF） algorithm has been frequently used since 1990s.A modified spectral feature fitting method is introduced here,which can solve some drawback of the general algorithm.The method mentioned here combines SFF with user-defined constraints in spectral absorption feature to extract more accurate target information from hyperspectral image. Two experiments are presented herein,in which three algorithms are used to obtain mineral information from hyperspectral data with different space resolution and SNR.Muscovite,calcite and chlorite etc.are extracted by general SFF,modified SFF and spectral angle mapping（SAM） respectively,and the result indicates that modified SFF algorithm is more effective in differentiating subtle spectral feature and obtaining accurate mineral information.The experiments also demonstrate that the algorithm mentioned here is validated in mineral information extraction.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2011年第6期1639-1643,共5页
Spectroscopy and Spectral Analysis
基金
国家(863计划)重点项目(2008AA121103)
中国地质大调查项目(1212010816033)资助
关键词
高光谱遥感
光谱特征拟合
光谱角制图
矿物信息提取
Hyperspectral remote sensing
Spectral feature fitting（SFF）
Spectral angle mapping（SAM）
Mineral information extraction
