title: Local rank-based spatial information for improvement of remote sensing hyperspectral imaging resolution.
abstract: This paper shows the effect of using local rank and selectivity constraints based on spatial information of spectroscopic images to increase the performance of Multivariate Curve Resolution (MCR) methods and to decrease the ambiguity of final results. Fixed Size Image Window-Evolving Factor Analysis (FSIW-EFA) is applied to discover which pixels are more suitable for the application of local rank constraints. An automated method to help in setting appropriate threshold values for the application of FSIW-EFA, based on global and local use of Singular Value Decomposition (SVD) is proposed. Additional use of correlation coefficients between selected reference spectra and pixel spectra of the image is shown to provide an alternative way for the application of the selectivity constraint in spectroscopic images for the first time. This alternative method resulted to be satisfactory when pure pixels exist.
authors.affiliation: IDAEA-CSIC, Jordi Girona 18, Barcelona 08034, Spain.
authors.forename: Xin
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Chemometrics Group, Department of Analytical Chemistry, Universitat de Barcelona, Diagonal 645, Barcelona 08028, Spain.
authors.forename: Anna de
authors.initials: Ad
authors.lastname: Juan
authors.affiliation: IDAEA-CSIC, Jordi Girona 18, Barcelona 08034, Spain. Electronic address: Roma.Tauler@idaea.csic.es.
authors.forename: Romà
authors.initials: R
authors.lastname: Tauler
keywords: Hyperspectral imaging; Local rank constraints; MCR; Remote sensing; Rotation ambiguity