Hyperspectral Imaging and Applications

Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue "Hyperspectral Imaging and Applications"...

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Médium:	E-kniha
Jazyk:	angličtina
Vydáno:	Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
Témata:	90° yaw imaging adaptive window Africa agroforestry AHS airborne laser scanning algebraic multigrid methods anomaly detection AVIRIS band expansion process (BEP) band grouping band selection band selection (BS) band subset selection (BSS) biodiversity class imbalance classification composite kernel constrained energy minimization constrained energy minimization (CEM) correlation band expansion process (CBEP) data fusion data integration data unmixing data-guided constraints deep belief networks deep learning deep pipelined background statistics Dunhuang site endmember extraction ensemble learning evenness fire severity Gram–Schmidt orthogonalization graph hashing ensemble hierarchical feature high-level synthesis History of engineering and technology HyMap hyperspectral hyperspectral classification hyperspectral compression hyperspectral detection hyperspectral image hyperspectral image (HSI) hyperspectral image classification hyperspectral imagery hyperspectral images (HSIs) hyperspectral imaging hyperspectral pansharpening hyperspectral unmixing image enhancement image fusion imaging spectroscopy in situ measurements intrinsic image decomposition irradiance-based method iterative algorithm iterative CEM (ICEM) KSVD label propagation linearly constrained minimum variance (LCMV) local abundance local summation RX detector (LS-RXD) lossy compression machine learning mineral mapping minimum noise fraction multiscale spatial information multiscale union regions adaptive sparse representation (MURASR) nonlinear band expansion (NBE) nonnegative matrix factorization nuclear norm on-board compression optical spectral region orthogonal projections Otsu’s method panchromatic panchromatic image parallel processing peatland progressive sample processing (PSP) prototype space raw material real-time processing recursive anomaly detection reflectance-based method remote sensing rolling guidance filtering (RGF) rotation forest semi-supervised learning semi-supervised local discriminant analysis sequential LCMV-BSS (SQ LCMV-BSS) sliding window sparse coding sparse unmixing sparseness spectral mixture analysis spectral variability spectral-spatial classification sprout detection structure tensor successive LCMV-BSS (SC LCMV-BSS) superpixel SVM target detection Technology, Engineering, Agriculture, Industrial processes Technology: general issues terrestrial hyperspectral imaging texture feature enhancement thermal infrared spectral region tree species tree-based ensemble vegetation type vicarious calibration vineyard water stress weighted fusion weighted least squares filter
ISBN:	9783039215232, 9783039215225, 3039215221, 303921523X
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Popis
Shrnutí:	Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue "Hyperspectral Imaging and Applications" is to publish new ideas and technologies to facilitate the utility of hyperspectral imaging in data exploitation and to further explore its potential in different applications. This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories with the number of papers published in every category included in its open parenthesis. 1. Data Unmixing (2 papers)2. Spectral variability (2 papers)3. Target Detection (3 papers)4. Hyperspectral Image Classification (6 papers)5. Band Selection (2 papers)6. Data Fusion (2 papers)7. Applications (8 papers) Under every category each paper is briefly summarized by a short description so that readers can quickly grab its content to find what they are interested in.
ISBN:	9783039215232 9783039215225 3039215221 303921523X
DOI:	10.3390/books978-3-03921-523-2