[00922] Matrix Factorization for Change Detection in HyperSpectral Images
Session Time & Room : 3E (Aug.23, 17:40-19:20) @G304
Type : Contributed Talk
Abstract : When hyperspectral images are analyzed, a big amount of data needs to be processed and therefore, specific matrix factorization algorithms are used to express the original problem in suitable subspacesWe show some recent results derived also by using spatial and spectral functions to compute a lower rank approximation of the original matrix and to measure the reconstruction error between the input image and the approximate one, with applications to the task of change-detection.
