B-HYCA: Blind hyperspectral compressive sensing

Compressive Sensing has raised as a very useful way to save costs in the acquisition equipment due to the fact that with this technique we can measure the signal in an already compressed form. This is very interesting in hyperspectral applications due to the large amount of data that the hyper-spectral sensors collect, store and transmit to the ground stations. Over the last years many compressive sensing methods have been applied to hyperspectral images, and others have been proposed for exploiting the unique features of this kind of images. Over the last years, many techniques have been proposed to perform compressive sensing in hyperspectral imaging. One of them is the Hyperspectral Coded Aperture (HYCA), which exploits two characteristics of hyper-spectral imagery: 1) the hyperspectral vectors belong to a low dimensional subspace, and 2) the data cube components exhibit very high correlation in the spatial and in the spectral domains. However, HYCA requires the knowledge of the subspace in advance, which, very often, may compromise its applicability. In this paper it is presented a new technique similar to HYCA which does not require the knowledge of the subspace in advance; the proposed technique is termed blind HYCA (B-HYCA) and it performs a form of blind hyperspectral compressed sensing.