Hakki Alparslan Ilgin

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Hyperspectral sensors generate images in narrow bands in continuous manner with hundreds of spectral bands. The data with large number of bands require more processing power to classify. To decrease the redundancy in hyperspectral images and increase classifying efficiency with less number of bands, dimension reduction techniques are applied. In this paper,(More)
Compressive Sensing (CS) is a technique that suggests the possibility of reconstruction of a signal vector using much smaller linear measurements than its dimension. Sparse signals are acquired in vectors using sensing matrices. If the signals are sparse enough the original signal can be reconstructed successfully. In CS applications while the signal can be(More)
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