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" is to pu...
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| Materialtyp: | Online |
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| Språk: | engelska |
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MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Länkar: | ONIX_20220812_9783039215225_16 |
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| _version_ | 1869524025672204288 |
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| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-91137 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-911372024-04-09T23:16:10Z Hyperspectral Imaging and Applications Chang, Chein-I Song, Meiping Zhang, Junping Wu, Chao-Cheng 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology 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. 2022-08-12T12:44:12Z 2022-08-12T12:44:12Z 2022 book ONIX_20220812_9783039215225_16 9783039215225 9783039215232 https://directory.doabooks.org/handle/20.500.12854/91137 eng image/png Attribution 4.0 International https://mdpi.com/books/pdfview/book/5770 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03921-523-2 10.3390/books978-3-03921-523-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039215225 9783039215232 632 Basel open access |
| spellingShingle | 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Hyperspectral Imaging and Applications |
| title | Hyperspectral Imaging and Applications |
| title_full | Hyperspectral Imaging and Applications |
| title_fullStr | Hyperspectral Imaging and Applications |
| title_full_unstemmed | Hyperspectral Imaging and Applications |
| title_short | Hyperspectral Imaging and Applications |
| title_sort | hyperspectral imaging and applications |
| topic | 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | 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 thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20220812_9783039215225_16 |