Remote Sensing for Target Object Detection and Identification

• Main Author: Ziemann, Amanda (auth)
• Other Authors: Vivone, Gemine (auth), Addesso, Paolo (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: Geography; satellite videos; nonconvex tensor robust principle component analysis; infrared; phase unwrapping; non-independent and identical distribution (non-i.i.d.) mixture of Gaussians; dictionary construction; Color Markov Chain; convolutional neural networks; ground-based detection; hazard prevention; ADMM; observability; pixel-tracking; multi-scale pyramidal features; thermal infrared target tracking; visible; component mixture model; hyperspectral imagery; flux density; particle filter framework; processor; detecting distance; rivers water-flow elevation estimation; non-convex optimization; convolutional neural networks (CNNs); infrared small-faint target detection; target detection; infrared imaging; synthetic aperture radar (SAR); low-rank representation; local prior analysis; remote sensing images; hardware architecture; remote sensing image; unsupervised saliency model; variational Bayesian; SAR; hyperspectral; anomaly detection; infrared small target detection; object detection; partial sum of the tensor nuclear norm; superpixel segmentation; multi-model; deep learning; mask sparse representation; oil tank detection; tiny and dim target detection; HSI reconstruction; part-based; semantic features; region proposals; unmanned aerial vehicle; object matching; hidden danger identification; remote sensing imagery; target identification; Lp-norm constraint; low rank sparse decomposition; bottom-up and top-down; contextual information; multi-scale strategies; sparse coding; very-high-resolution (VHR) remote sensing imagery; vehicle detection; alternating direction method of multipliers; adaptive weighting; flood hazard; tower failure; earth entry vehicle
• Online Access: DOAB: download the publication; DOAB: description of the publication

Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amount of data acquired by sensors mounted on satellite, airborne, and unmanned aerial vehicle (UAV) platforms. This book promotes papers exploiting different remote sensing data for target object detection and identification, such as synthetic aperture radar (SAR) imaging and multispectral and hyperspectral imaging. Several cutting-edge contributions, which provide examples of how to select of a technology or another depending on the specific application, will be detailed.