Book ; Online: Hyperspectral Imaging and Applications
2022
| Keywords | Technology: general issues ; History of engineering & technology ; biodiversity ; peatland ; vegetation type ; classification ; hyperspectral ; in situ measurements ; hyperspectral image (HSI) ; multiscale union regions adaptive sparse representation (MURASR) ; multiscale spatial information ; imaging spectroscopy ; airborne laser scanning ; minimum noise fraction ; class imbalance ; Africa ; agroforestry ; tree species ; hyperspectral unmixing ; endmember extraction ; band selection ; spectral variability ; prototype space ; ensemble learning ; rotation forest ; semi-supervised local discriminant analysis ; optical spectral region ; thermal infrared spectral region ; mineral mapping ; data integration ; HyMap ; AHS ; raw material ; remote sensing ; nonnegative matrix factorization ; data-guided constraints ; sparseness ; evenness ; hashing ensemble ; hierarchical feature ; hyperspectral classification ; band expansion process (BEP) ; constrained energy minimization (CEM) ; correlation band expansion process (CBEP) ; iterative CEM (ICEM) ; nonlinear band expansion (NBE) ; Otsu's method ; sparse unmixing ; local abundance ; nuclear norm ; hyperspectral detection ; target detection ; sprout detection ; constrained energy minimization ; iterative algorithm ; adaptive window ; hyperspectral imagery ; recursive anomaly detection ; local summation RX detector (LS-RXD) ; sliding window ; band selection (BS) ; band subset selection (BSS) ; hyperspectral image classification ; linearly constrained minimum variance (LCMV) ; successive LCMV-BSS (SC LCMV-BSS) ; sequential LCMV-BSS (SQ LCMV-BSS) ; vicarious calibration ; reflectance-based method ; irradiance-based method ; Dunhuang site ; 90° yaw imaging ; terrestrial hyperspectral imaging ; vineyard ; water stress ; machine learning ; tree-based ensemble ; progressive sample processing (PSP) ; real-time processing ; image fusion ; hyperspectral image ; panchromatic image ; structure tensor ; image enhancement ; weighted fusion ; spectral mixture analysis ; fire severity ; AVIRIS ; deep belief networks ; deep learning ; texture feature enhancement ; band grouping ; hyperspectral compression ; lossy compression ; on-board compression ; orthogonal projections ; Gram-Schmidt orthogonalization ; parallel processing ; anomaly detection ; sparse coding ; KSVD ; hyperspectral images (HSIs) ; SVM ; composite kernel ; algebraic multigrid methods ; hyperspectral pansharpening ; panchromatic ; intrinsic image decomposition ; weighted least squares filter ; spectral-spatial classification ; label propagation ; superpixel ; semi-supervised learning ; rolling guidance filtering (RGF) ; graph ; deep pipelined background statistics ; high-level synthesis ; data fusion ; data unmixing ; hyperspectral imaging |
|---|---|
| Language | 0|e |
| Size | 1 electronic resource (632 pages) |
| Publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| Publishing place | Basel |
| Document type | Book ; Online |
| Note | English ; Open Access |
| HBZ-ID | HT021613101 |
| ISBN | 9783039215232 ; 303921523X |
| Database | ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture |
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