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Remote Sensing
Volume 11
Issue 5
10.3390/rs11050559
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Article

Infrared Small Target Detection Based on Non-Convex Optimization with Lp-Norm Constraint

by
Tianfang Zhang
1,
Hao Wu
1,
Yuhan Liu
1,
Lingbing Peng
1,
Chunping Yang
1 and
Zhenming Peng
1,2,*
1
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
2
Center for Information Geoscience, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(5), 559; https://doi.org/10.3390/rs11050559
Submission received: 31 January 2019 / Revised: 24 February 2019 / Accepted: 4 March 2019 / Published: 7 March 2019
(This article belongs to the Special Issue Remote Sensing for Target Object Detection and Identification)
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Abstract

The infrared search and track (IRST) system has been widely used, and the field of infrared small target detection has also received much attention. Based on this background, this paper proposes a novel infrared small target detection method based on non-convex optimization with Lp-norm constraint (NOLC). The NOLC method strengthens the sparse item constraint with Lp-norm while appropriately scaling the constraints on low-rank item, so the NP-hard problem is transformed into a non-convex optimization problem. First, the infrared image is converted into a patch image and is secondly solved by the alternating direction method of multipliers (ADMM). In this paper, an efficient solver is given by improving the convergence strategy. The experiment shows that NOLC can accurately detect the target and greatly suppress the background, and the advantages of the NOLC method in detection efficiency and computational efficiency are verified.
Keywords: low rank sparse decomposition; Lp-norm constraint; non-convex optimization; alternating direction method of multipliers; infrared small target detection low rank sparse decomposition; Lp-norm constraint; non-convex optimization; alternating direction method of multipliers; infrared small target detection
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MDPI and ACS Style

Zhang, T.; Wu, H.; Liu, Y.; Peng, L.; Yang, C.; Peng, Z. Infrared Small Target Detection Based on Non-Convex Optimization with Lp-Norm Constraint. Remote Sens. 2019, 11, 559. https://doi.org/10.3390/rs11050559

AMA Style

Zhang T, Wu H, Liu Y, Peng L, Yang C, Peng Z. Infrared Small Target Detection Based on Non-Convex Optimization with Lp-Norm Constraint. Remote Sensing. 2019; 11(5):559. https://doi.org/10.3390/rs11050559

Chicago/Turabian Style

Zhang, Tianfang, Hao Wu, Yuhan Liu, Lingbing Peng, Chunping Yang, and Zhenming Peng. 2019. "Infrared Small Target Detection Based on Non-Convex Optimization with Lp-Norm Constraint" Remote Sensing 11, no. 5: 559. https://doi.org/10.3390/rs11050559

APA Style

Zhang, T., Wu, H., Liu, Y., Peng, L., Yang, C., & Peng, Z. (2019). Infrared Small Target Detection Based on Non-Convex Optimization with Lp-Norm Constraint. Remote Sensing, 11(5), 559. https://doi.org/10.3390/rs11050559

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