Advances in Hyperspectral Data Exploitation

• Other Authors: Chang, Chein-I (Editor), Song, Meiping (Editor), Yu, Chunyan (Editor), Wang, Yulei (Editor), Yu, Haoyang (Editor), Li, Jiaojiao (Editor), Wang, Lin (Editor), Li, Hsiao-Chi (Editor), Li, Xiaorun (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Subjects: Technology: general issues; History of engineering & technology; hyperspectral image few-shot classification; deep learning; meta-learning; relation network; convolutional neural network; constrained-target optimal index factor band selection (CTOIFBS); hyperspectral image; underwater spectral imaging system; underwater hyperspectral target detection; band selection (BS); constrained energy minimization (CEM); lightweight convolutional neural networks; hyperspectral imagery classification; transfer learning; air temperature; spatial measurement; FTIR; MWIR; carbon dioxide absorption; target detection; coffee beans; insect damage; hyperspectral imaging; band selection; visualization; color formation models; multispectral image; image fusion; joint tensor decomposition; anomaly detection; constrained sparse representation; hyperspectral imagery; moving target detection; spatio-temporal processing; hyperspectral remote sensing; image classification; constraint representation; superpixel segmentation; multiscale decision fusion; plug-and-play; denoising; nonlinear unmixing; spectral reconstruction; residual augmented attentional u-shape network; spatial augmented attention; channel augmented attention; boundary-aware constraint; atmospheric transmittance; temperature; emissivity; separation; midwave infrared; hyperspectral images; hyperspectral image super-resolution; data fusion; spectral-spatial residual network; self-supervised training; hyperspectral; vegetation; generative adversarial network; data augmentation; classification; rice leaf blast; hyperspectral imaging data; deep convolutional neural networks; fused features; evolutionary computation; heuristic algorithms; machine learning; unmanned aerial vehicles (UAVs); vegetation mapping; upland swamps; mine environment; rice; rice leaf folder; hyperspectral image classification; change detection; self-supervised learning; attention mechanism; multi-source image fusion; SFIM; least square estimation; spatial filter; hyperspectral imaging (HSI); hyperspectral target detection; hyperspectral reconstruction; hyperspectral unmixing
• Online Access: DOAB: download the publication; DOAB: description of the publication

Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such appli...