Hyperspectral Super-Resolution with Spectral Unmixing Constraints
نویسندگان
چکیده
منابع مشابه
Hyperspectral Super-Resolution with Spectral Unmixing Constraints
Hyperspectral sensors capture a portion of the visible and near-infrared spectrum with many narrow spectral bands. This makes it possible to better discriminate objects based on their reflectance spectra and to derive more detailed object properties. For technical reasons, the high spectral resolution comes at the cost of lower spatial resolution. To mitigate that problem, one may combine such ...
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Existing hyperspectral imaging systems produce low spatial resolution images due to hardware constraints. We propose a sparse representation based approach for hyperspectral image super-resolution. The proposed approach first extracts distinct reflectance spectra of the scene from the available hyperspectral image. Then, the signal sparsity, non-negativity and the spatial structure in the scene...
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Hyperspectral (HS) super-resolution reconstruction is an ill-posed inversion problem, for which the solution from reconstruction constraint is not unique. To address this, an HS image super-resolution method is proposed to first utilize the joint regulation of spatial and spectral nonlocal similarities. We then fused the HS and panchromatic images with sparse regulation. With these two regulati...
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The spectral dimension of hyperspectral imaging (HSI) systems plays a fundamental role in numerous terrestrial and earth observation applications, including spectral unmixing, target detection, and classification among others. However, in several cases the spectral resolution of HSI systems is sacrificed for the shake of spatial resolution, as such in the case of snapshot spectral imaging syste...
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2017
ISSN: 2072-4292
DOI: 10.3390/rs9111196