RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring
Infrared small target detection is a crucial technology in both military and civilian applications, including surveillance, security, defense, and combat. However, accurate infrared detection of small targets in real-time is challenging due to their small size and similarity in gray level and textur...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/11/2922 |
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| author | Yuanyuan Chen Huiqian Wang Yu Pang Jinhui Han En Mou Enling Cao |
| author_facet | Yuanyuan Chen Huiqian Wang Yu Pang Jinhui Han En Mou Enling Cao |
| author_sort | Yuanyuan Chen |
| collection | DOAJ |
| description | Infrared small target detection is a crucial technology in both military and civilian applications, including surveillance, security, defense, and combat. However, accurate infrared detection of small targets in real-time is challenging due to their small size and similarity in gray level and texture with the surrounding environment, as well as interference from the infrared imaging systems in unmanned aerial vehicles (UAVs). This article proposes a weighted local contrast method based on the contrast mechanism of the human visual system. Initially, a combined contrast ratio is defined that stems from the pixel-level divergence between the target and its neighboring pixels. Then, an improved regional intensity level is used to establish a weight function with the concept of ratio difference combination, which can effectively suppress complex backgrounds and random noise. In the final step, the contrast and weight functions are combined to create the final weighted local contrast method (WRDLCM). This method does not require any preconditioning and can enhance the target while suppressing background interference. Additionally, it is capable of detecting small targets even when their scale changes. In the experimental section, our algorithm was compared with some popular methods, and the experimental findings indicated that our method showed strong detection capability based on the commonly used performance indicators of the ROC curve, SCRG, and BSF, especially in low signal-to-noise ratio situations. In addition, unlike deep learning, this method is appropriate for small sample sizes and is easy to implement on FPGA hardware. |
| format | Article |
| id | doaj-art-e9e6e65fe477443785f33e89a6f32ba6 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-e9e6e65fe477443785f33e89a6f32ba62025-02-10T13:06:55ZengMDPI AGRemote Sensing2072-42922023-06-011511292210.3390/rs15112922RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety MonitoringYuanyuan Chen0Huiqian Wang1Yu Pang2Jinhui Han3En Mou4Enling Cao5School of Communication and Information Engineering, Chongqing University of Posts and Telecommunication, Chongqing 400065, ChinaSchool of Optoelectronic Engineering, Chongqing University of Posts and Telecommunication, Chongqing 400065, ChinaSchool of Optoelectronic Engineering, Chongqing University of Posts and Telecommunication, Chongqing 400065, ChinaCollege of Physics and Telecommunication Engineering, Zhoukou Normal University, Zhoukou 466001, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunication, Chongqing 400065, ChinaSchool of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaInfrared small target detection is a crucial technology in both military and civilian applications, including surveillance, security, defense, and combat. However, accurate infrared detection of small targets in real-time is challenging due to their small size and similarity in gray level and texture with the surrounding environment, as well as interference from the infrared imaging systems in unmanned aerial vehicles (UAVs). This article proposes a weighted local contrast method based on the contrast mechanism of the human visual system. Initially, a combined contrast ratio is defined that stems from the pixel-level divergence between the target and its neighboring pixels. Then, an improved regional intensity level is used to establish a weight function with the concept of ratio difference combination, which can effectively suppress complex backgrounds and random noise. In the final step, the contrast and weight functions are combined to create the final weighted local contrast method (WRDLCM). This method does not require any preconditioning and can enhance the target while suppressing background interference. Additionally, it is capable of detecting small targets even when their scale changes. In the experimental section, our algorithm was compared with some popular methods, and the experimental findings indicated that our method showed strong detection capability based on the commonly used performance indicators of the ROC curve, SCRG, and BSF, especially in low signal-to-noise ratio situations. In addition, unlike deep learning, this method is appropriate for small sample sizes and is easy to implement on FPGA hardware.https://www.mdpi.com/2072-4292/15/11/2922IR small targethuman visual systemlocal contrastimproved regional intensity level (IRIL) |
| spellingShingle | Yuanyuan Chen Huiqian Wang Yu Pang Jinhui Han En Mou Enling Cao RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring Remote Sensing IR small target human visual system local contrast improved regional intensity level (IRIL) |
| title | RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring |
| title_full | RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring |
| title_fullStr | RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring |
| title_full_unstemmed | RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring |
| title_short | RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring |
| title_sort | retracted an infrared small target detection method based on a weighted human visual comparison mechanism for safety monitoring |
| topic | IR small target human visual system local contrast improved regional intensity level (IRIL) |
| url | https://www.mdpi.com/2072-4292/15/11/2922 |
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