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Many standard multivariate detection algorithms used in hyperspectral image analysis (e.g., Mahalanobis distance, matched filter) rely on the inverse covariance matrix, C−1. The inverse covariance matrix has a clear geometrical interpretation as a “whitening” operator that transforms the original measurement coordinates such that the background data distribution is uncorrelated with equal variance...
In the area of hyperspectral image detection, Constrained Energy Minimization (CEM) algorithm has received considerable interest recently. However, it is very sensitive to noise and can only detect one target at one time. In order to solve this problem, Winner-Take-All Constrained Energy Minimization (WTACEM) was proposed. Based on it, we propose a modified multi-target detection approach. We study...
In this paper, we try to identify and quantify the chemical species present on the surface of planet Mars with the help of hyperspectral images provided by the instrument OMEGA. For this purpose, we suppose that the spectrum of each pixel is a linear mixture of the spectra of different endmembers. From this linear mixture hypothesis, our work is divided into two steps. Firstly, we propose a new unsupervised...
In this paper, we try to identify and quantify the chemical species present on the surface of planet Mars with the help of hyperspectral images provided by the instrument OMEGA (Bibring et al., 2004). For this purpose, we suppose that the spectrum of each pixel is a linear mixture of the spectra of different endmembers. From this linear mixture hypothesis, our work is divided into two steps. Firstly,...
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