The Analysis of Error Sources for SAM and Its Improvement Algorithms
TANG Hong1, DU Pei-jun1，2, FANG Tao1, SHI Peng-fei1
1.The Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China 2.The Environment and Surveying Institute, China University of Mining and Technology, Xuzhou 221008, China
Abstract：Based on the analysis of the error sources for spectral angle mapping (SAM), several key elements are pointed out, i.e.the change of wave band location, the change of the attribution ratio, the random change of attribution, and the whole translation of wave band.After the above-mentioned four error sources are analyzed, the authors present several improvement algorithms, viz. calculating the spectral angle with grouping, normalization and intersection.The grouping method can resolve the pseudo-similar problem, because it considers both spectral global features and local features.Calculating spectral angle with normalization restrains those random errors in original data by normalizing the spectral vectors.The intersection method can eliminate the error elicited by the whole wave translation.Therefore, it can be employed to correctly identify spectral class.Experiments show that those improvement algorithms are effective and can be used to process spectral data with errors.
唐 宏1, 杜培军1, ２，方 涛1, 施鹏飞1 . 光谱角制图模型的误差源分析与改进算法[J]. 光谱学与光谱分析, 2005, 25(08): 1180-1183.
TANG Hong1, DU Pei-jun1，2, FANG Tao1, SHI Peng-fei1 . The Analysis of Error Sources for SAM and Its Improvement Algorithms. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(08): 1180-1183.
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