LEADER 06755nam 2201825z- 450 001 9910585941603321 005 20231214133633.0 035 $a(CKB)5600000000483066 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/91137 035 $a(EXLCZ)995600000000483066 100 $a20202208d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHyperspectral Imaging and Applications 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (632 p.) 311 $a3-03921-522-1 311 $a3-03921-523-X 330 $aDue 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. 606 $aTechnology: general issues$2bicssc 606 $aHistory of engineering & technology$2bicssc 610 $abiodiversity 610 $apeatland 610 $avegetation type 610 $aclassification 610 $ahyperspectral 610 $ain situ measurements 610 $ahyperspectral image (HSI) 610 $amultiscale union regions adaptive sparse representation (MURASR) 610 $amultiscale spatial information 610 $aimaging spectroscopy 610 $aairborne laser scanning 610 $aminimum noise fraction 610 $aclass imbalance 610 $aAfrica 610 $aagroforestry 610 $atree species 610 $ahyperspectral unmixing 610 $aendmember extraction 610 $aband selection 610 $aspectral variability 610 $aprototype space 610 $aensemble learning 610 $arotation forest 610 $asemi-supervised local discriminant analysis 610 $aoptical spectral region 610 $athermal infrared spectral region 610 $amineral mapping 610 $adata integration 610 $aHyMap 610 $aAHS 610 $araw material 610 $aremote sensing 610 $anonnegative matrix factorization 610 $adata-guided constraints 610 $asparseness 610 $aevenness 610 $ahashing ensemble 610 $ahierarchical feature 610 $ahyperspectral classification 610 $aband expansion process (BEP) 610 $aconstrained energy minimization (CEM) 610 $acorrelation band expansion process (CBEP) 610 $aiterative CEM (ICEM) 610 $anonlinear band expansion (NBE) 610 $aOtsu?s method 610 $asparse unmixing 610 $alocal abundance 610 $anuclear norm 610 $ahyperspectral detection 610 $atarget detection 610 $asprout detection 610 $aconstrained energy minimization 610 $aiterative algorithm 610 $aadaptive window 610 $ahyperspectral imagery 610 $arecursive anomaly detection 610 $alocal summation RX detector (LS-RXD) 610 $asliding window 610 $aband selection (BS) 610 $aband subset selection (BSS) 610 $ahyperspectral image classification 610 $alinearly constrained minimum variance (LCMV) 610 $asuccessive LCMV-BSS (SC LCMV-BSS) 610 $asequential LCMV-BSS (SQ LCMV-BSS) 610 $avicarious calibration 610 $areflectance-based method 610 $airradiance-based method 610 $aDunhuang site 610 $a90° yaw imaging 610 $aterrestrial hyperspectral imaging 610 $avineyard 610 $awater stress 610 $amachine learning 610 $atree-based ensemble 610 $aprogressive sample processing (PSP) 610 $areal-time processing 610 $aimage fusion 610 $ahyperspectral image 610 $apanchromatic image 610 $astructure tensor 610 $aimage enhancement 610 $aweighted fusion 610 $aspectral mixture analysis 610 $afire severity 610 $aAVIRIS 610 $adeep belief networks 610 $adeep learning 610 $atexture feature enhancement 610 $aband grouping 610 $ahyperspectral compression 610 $alossy compression 610 $aon-board compression 610 $aorthogonal projections 610 $aGram?Schmidt orthogonalization 610 $aparallel processing 610 $aanomaly detection 610 $asparse coding 610 $aKSVD 610 $ahyperspectral images (HSIs) 610 $aSVM 610 $acomposite kernel 610 $aalgebraic multigrid methods 610 $ahyperspectral pansharpening 610 $apanchromatic 610 $aintrinsic image decomposition 610 $aweighted least squares filter 610 $aspectral-spatial classification 610 $alabel propagation 610 $asuperpixel 610 $asemi-supervised learning 610 $arolling guidance filtering (RGF) 610 $agraph 610 $adeep pipelined background statistics 610 $ahigh-level synthesis 610 $adata fusion 610 $adata unmixing 610 $ahyperspectral imaging 615 7$aTechnology: general issues 615 7$aHistory of engineering & technology 700 $aChang$b Chein-I$4edt$0763028 702 $aSong$b Meiping$4edt 702 $aZhang$b Junping$4edt 702 $aWu$b Chao-Cheng$4edt 702 $aChang$b Chein-I$4oth 702 $aSong$b Meiping$4oth 702 $aZhang$b Junping$4oth 702 $aWu$b Chao-Cheng$4oth 906 $aBOOK 912 $a9910585941603321 996 $aHyperspectral Imaging and Applications$93035981 997 $aUNINA