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We review several detection strategies that account for the possible sparsity of target sources in data cubes. The considered sparsity can exist in the data acquisition space, or in some transform domain. Theoretical aspects of the detection tests are first described. Emphasis is then put on practical issues that may arise in hyperspectral data, such as spatio-spectral dependencies or very low Signal-to-Noise...
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