Hyperspectral Imaging and Applications
| Hyperspectral Imaging and Applications |
| Autore | Chang Chein-I |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (632 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
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 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 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 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910585941603321 |
Chang Chein-I
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 1 / Qi Wang |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (414 pages) |
| Soggetto topico | Computer science |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN |
9783038976851
3038976857 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755603321 |
Wang Qi
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang
| Learning to Understand Remote Sensing Images: Volume 2 / Qi Wang |
| Autore | Wang Qi |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (363 pages) |
| Soggetto non controllato |
metadata
image classification sensitivity analysis ROI detection residual learning image alignment adaptive convolutional kernels Hough transform class imbalance land surface temperature inundation mapping multiscale representation object-based convolutional neural networks scene classification morphological profiles hyperedge weight estimation hyperparameter sparse representation semantic segmentation vehicle classification flood Landsat imagery target detection multi-sensor building damage detection optimized kernel minimum noise fraction (OKMNF) sea-land segmentation nonlinear classification land use SAR imagery anti-noise transfer network sub-pixel change detection Radon transform segmentation remote sensing image retrieval TensorFlow convolutional neural network particle swarm optimization optical sensors machine learning mixed pixel optical remotely sensed images object-based image analysis very high resolution images single stream optimization ship detection ice concentration online learning manifold ranking dictionary learning urban surface water extraction saliency detection spatial attraction model (SAM) quality assessment Fuzzy-GA decision making system land cover change multi-view canonical correlation analysis ensemble land cover semantic labeling sparse representation dimensionality expansion speckle filters hyperspectral imagery fully convolutional network infrared image Siamese neural network Random Forests (RF) feature matching color matching geostationary satellite remote sensing image change feature analysis road detection deep learning aerial images image segmentation aerial image multi-sensor image matching HJ-1A/B CCD endmember extraction high resolution multi-scale clustering heterogeneous domain adaptation hard classification regional land cover hypergraph learning automatic cluster number determination dilated convolution MSER semi-supervised learning gate Synthetic Aperture Radar (SAR) downscaling conditional random fields urban heat island hyperspectral image remote sensing image correction skip connection ISPRS spatial distribution geo-referencing Support Vector Machine (SVM) very high resolution (VHR) satellite image classification ensemble learning synthetic aperture radar conservation convolutional neural network (CNN) THEOS visible light and infrared integrated camera vehicle localization structured sparsity texture analysis DSFATN CNN image registration UAV unsupervised classification SVMs SAR image fuzzy neural network dimensionality reduction GeoEye-1 feature extraction sub-pixel energy distribution optimizing saliency analysis deep convolutional neural networks sparse and low-rank graph hyperspectral remote sensing tensor low-rank approximation optimal transport SELF spatiotemporal context learning Modest AdaBoost topic modelling multi-seasonal Segment-Tree Filtering locality information GF-4 PMS image fusion wavelet transform hashing machine learning techniques satellite images climate change road segmentation remote sensing tensor sparse decomposition Convolutional Neural Network (CNN) multi-task learning deep salient feature speckle canonical correlation weighted voting fully convolutional network (FCN) despeckling multispectral imagery ratio images linear spectral unmixing hyperspectral image classification multispectral images high resolution image multi-objective convolution neural network transfer learning 1-dimensional (1-D) threshold stability Landsat kernel method phase congruency subpixel mapping (SPM) tensor MODIS GSHHG database compressive sensing |
| ISBN |
9783038976998
3038976997 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367755503321 |
Wang Qi
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||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||