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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