Infrared Small-Target Detection Based on Background-Suppression Proximal Gradient and GPU Acceleration

Patch-based methods improve the performance of infrared small target detection, transforming the detection problem into a Low-Rank Sparse Decomposition (LRSD) problem. However, two challenges hinder the success of these methods: (1) The interference from strong edges of the background, and (2) the t...

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Vydané v:	Remote sensing (Basel, Switzerland) Ročník 15; číslo 22; s. 5424
Hlavní autori:	Hao, Xuying, Liu, Xianyuan, Liu, Yujia, Cui, Yi, Lei, Tao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.11.2023
Predmet:	Accuracy Algorithms approximate partial SVD Approximation bioinformatics Decomposition Deep learning Design False alarms GPU acceleration Graphics processing units Infrared imaging infrared small target detection methodology Methods proximal gradient remote sensing Signal processing solutions Sparsity Target detection Tracking systems China
ISSN:	2072-4292, 2072-4292
On-line prístup:	Získať plný text
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