Matrix-based subspace analysis with the general norm for image feature extraction

Abstract

Classical matrix-based subspace analysis tries to exploit the structured information (rows or columns) of images for extracting image features. However, it is not robust in dealing with contaminated data. In this paper, novel models for matrix-based subspace analysis with robust objective functions and general norms are developed to address this problem. In… (More)
DOI: 10.1007/s10044-017-0603-1

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