Hyperspectral Image Unmixing Incorporating Adjacency Information
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Beschreibung
While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials’ spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition methods taking into account spectral, spatial and global 3D adjacency information. This allows for faster and more accurate decomposition results.
While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials’ spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition methods taking into account spectral, spatial and global 3D adjacency information. This allows for faster and more accurate decomposition results.
Autor*in
Sebastian Bauer
Themen in »Hyperspectral Image Unmixing Incorporating Adjacency Information«
Spektrale Entmischung Nichtnegative Matrixzerlegung Hyperspektrale Bildverarbeitung Blinde Quellentrennung spectral unmixing nonnegative matrix factorization Hyperspectral image processing blind source separation