Single-Frame Infrared Small Target Detection by High Local Variance, Low-Rank and Sparse Decomposition

Single-Frame Infrared Small Target Detection (SF-IRSTD) has grown in popularity due to its broad application. Several models based on Low-Rank and Sparse Decomposition (LRSD) have been proposed recently and have shown excellent performance. Nevertheless, these methods regard the non-low-rank sparse...

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Vydané v:	IEEE transactions on geoscience and remote sensing Ročník 61; s. 1
Hlavní autori:	Liu, Yujia, Liu, Xianyuan, Hao, Xuying, Tang, Wei, Zhang, Sanxing, Lei, Tao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Decomposition Detection high local salience high local variance Image edge detection Infrared imagery Iterative methods low-rank and sparse decomposition Object detection Optimization Salience Single-frame infrared small target detection singular value Sparse matrices Target detection Tensors Three-dimensional displays
ISSN:	0196-2892, 1558-0644
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