This paper is concerned with deblurring and spectral analysis of ground-based astronomical images of space objects. A numerical approach is provided for deblurring and sparse unmixing of ground-based hyperspectral images (HSI) of objects taken through atmospheric turbulence. Hyperspectral imaging systems capture a 3D datacube (tensor) containing: 2D spatial information, and 1D spectral informat...

The problem of mixed pixels negatively affects the delineation of accurate surface water in Landsat Imagery. Linear spectral unmixing has been demonstrated to be a powerful technique for extracting surface materials at a sub-pixel scale. Therefore, in this paper, we propose an innovative low albedo fraction (LAF) method based on the idea of unconstrained linear spectral unmixing. The LAF stands...

The pixels of remote images often contain more than one distinct material (mixed pixels), and so their spectra are characterized by a mixture spectral signals. Since 1971, shared effort has enabled the development techniques for retrieving information from mixed pixels. most analyzed, implemented, employed procedure is unmixing. Among extensive literature on unmixing, nineteen reviews were iden...

The direct detection of exoplanets with high-contrast instruments can be boosted high spectral resolution. For integral field spectrographs yielding hyperspectral data, this means that the view consists diffracted starlight spectra and a spatially localized planet. Analysis usually relies on cross-correlation theoretical spectra. In purely blind-search context, supervised strategy biased model ...

Over the past decades, many methods have been proposed to solve linear or nonlinear mixing of spectra inside hyperspectral data. Due a relatively low spatial resolution imaging, each image pixel may contain from multiple materials. In turn, unmixing is finding these materials and their abundances. A few main approaches performing emerged, such as nonnegative matrix factorization (NMF), mixture ...