title: [Spectral similarity measure and retrieval based on the complete spectral reflectance and absorption feature--nonlinear spectral angle mapper].
abstract: A novel method for spectral similarity measure, which is called nonlinear spectral angle mapper, is presented. In this method, on one hand, nonlinear transformation and removing high relativity among bands are used through kernel PCA; on the other hand, the feature of both spectral reflection and absorption are combined in transformed space. At last, spectral angle mapper is used to measure spectral similarity. The authors' experiments show that this method is effective in spectral similarity retrieval.
authors.affiliation: The Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Tang
authors.forename: Tao
authors.initials: T
authors.lastname: Fang
authors.forename: Peng-fei
authors.initials: PF
authors.lastname: Shi
mesh_terms: D000042:Absorption; D000465:Algorithms; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D010087:Oxides / Q000737:chemistry*; D010363:Pattern Recognition, Automated; D013057:Spectrum Analysis / Q000379:methods / Q000706:statistics & numerical data*
chemical_list: D010087:Oxides