Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection
Detecting infrared (IR) small targets effectively and robustly is crucial for the tasks such as infrared searching and guarding. While methods based on the human vision system (HVS) have achieved great success in this field, detecting dim targets in complex backgrounds remains a challenge due to the...
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Format: | Article |
Language: | English |
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MDPI AG
2023-08-01
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Series: | Remote Sensing |
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Online Access: | https://www.mdpi.com/2072-4292/15/15/3839 |
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author | Liping Liu Yantao Wei Yue Wang Huang Yao Di Chen |
author_facet | Liping Liu Yantao Wei Yue Wang Huang Yao Di Chen |
author_sort | Liping Liu |
collection | DOAJ |
description | Detecting infrared (IR) small targets effectively and robustly is crucial for the tasks such as infrared searching and guarding. While methods based on the human vision system (HVS) have achieved great success in this field, detecting dim targets in complex backgrounds remains a challenge due to the multi-scale framework and over-simplified disparity calculations. In this paper, infrared small targets are detected with a novel local contrast measurement named double-layer patch-based contrast (DLPC). Firstly, we crafted an elaborated double-layer local contrast measure, to suppress the background, which can accurately measure the gray difference between the target and its surrounding complex background. Secondly, we calculated the absolute value of the grayscale difference between the target and the background in the diagonal directions as a weighting factor to further enhance the target. Then, an adaptive threshold on the DLPC was employed to extract the target from the IR image. The proposed method can detect small targets effectively with a fixed-scaled mask template while being computationally efficient. Experimental results in terms of background suppression factor (BSF), signal-to-clutter ratio gain (SCRG) and receiver operating characteristic (ROC) curve on five IR image datasets demonstrated that the proposed method has better detection performance compared to six state-of-the-art methods and is more robust in addressing complex backgrounds. |
first_indexed | 2024-03-11T00:17:47Z |
format | Article |
id | doaj.art-c62414487a4f4d7e8cea1f6ee3d29312 |
institution | Directory Open Access Journal |
issn | 2072-4292 |
language | English |
last_indexed | 2024-03-11T00:17:47Z |
publishDate | 2023-08-01 |
publisher | MDPI AG |
record_format | Article |
series | Remote Sensing |
spelling | doaj.art-c62414487a4f4d7e8cea1f6ee3d293122023-11-18T23:31:33ZengMDPI AGRemote Sensing2072-42922023-08-011515383910.3390/rs15153839Using Double-Layer Patch-Based Contrast for Infrared Small Target DetectionLiping Liu0Yantao Wei1Yue Wang2Huang Yao3Di Chen4Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, ChinaFaculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, ChinaFaculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, ChinaFaculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, ChinaFaculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, ChinaDetecting infrared (IR) small targets effectively and robustly is crucial for the tasks such as infrared searching and guarding. While methods based on the human vision system (HVS) have achieved great success in this field, detecting dim targets in complex backgrounds remains a challenge due to the multi-scale framework and over-simplified disparity calculations. In this paper, infrared small targets are detected with a novel local contrast measurement named double-layer patch-based contrast (DLPC). Firstly, we crafted an elaborated double-layer local contrast measure, to suppress the background, which can accurately measure the gray difference between the target and its surrounding complex background. Secondly, we calculated the absolute value of the grayscale difference between the target and the background in the diagonal directions as a weighting factor to further enhance the target. Then, an adaptive threshold on the DLPC was employed to extract the target from the IR image. The proposed method can detect small targets effectively with a fixed-scaled mask template while being computationally efficient. Experimental results in terms of background suppression factor (BSF), signal-to-clutter ratio gain (SCRG) and receiver operating characteristic (ROC) curve on five IR image datasets demonstrated that the proposed method has better detection performance compared to six state-of-the-art methods and is more robust in addressing complex backgrounds.https://www.mdpi.com/2072-4292/15/15/3839infrared imagetarget detectionlocal contrastdouble-layer |
spellingShingle | Liping Liu Yantao Wei Yue Wang Huang Yao Di Chen Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection Remote Sensing infrared image target detection local contrast double-layer |
title | Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection |
title_full | Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection |
title_fullStr | Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection |
title_full_unstemmed | Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection |
title_short | Using Double-Layer Patch-Based Contrast for Infrared Small Target Detection |
title_sort | using double layer patch based contrast for infrared small target detection |
topic | infrared image target detection local contrast double-layer |
url | https://www.mdpi.com/2072-4292/15/15/3839 |
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