A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation
In infrared small target detection, the infrared patch image (IPI)-model-based methods produce better results than other popular approaches (such as max-mean, top-hat, and human visual system) but in some extreme cases it suffers from long processing times and inconsistent performance. In order to o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/19/7327 |
| _version_ | 1797476967266648064 |
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| author | Tengyan Xi Lihua Yuan Quanbin Sun |
| author_facet | Tengyan Xi Lihua Yuan Quanbin Sun |
| author_sort | Tengyan Xi |
| collection | DOAJ |
| description | In infrared small target detection, the infrared patch image (IPI)-model-based methods produce better results than other popular approaches (such as max-mean, top-hat, and human visual system) but in some extreme cases it suffers from long processing times and inconsistent performance. In order to overcome these issues, we propose a novel approach of dividing the traditional target detection process into two steps: suppression of background noise and elimination of clutter. The workflow consists of four steps: after importing the images, the second step applies the alternating direction multiplier method to preliminarily remove the background. Comparatively to the IPI model, this step does not require sliding patches, resulting in a significant reduction in processing time. To eliminate residual noise and clutter, the interim results from morphological filtering are then processed in step 3 through an improved new top-hat transformation, using a threefold structuring element. The final step is thresholding segmentation, which uses an adaptive threshold algorithm. Compared with IPI and the new top-hat methods, as well as some other widely used methods, our approach was able to detect infrared targets more efficiently (90% less computational time) and consistently (no sudden performance drop). |
| first_indexed | 2024-03-09T21:11:18Z |
| format | Article |
| id | doaj.art-a37b0736accd48ee98dab2ed080839c3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:11:18Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a37b0736accd48ee98dab2ed080839c32023-11-23T21:47:29ZengMDPI AGSensors1424-82202022-09-012219732710.3390/s22197327A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat TransformationTengyan Xi0Lihua Yuan1Quanbin Sun2Key Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hang Kong University, Nanchang 330031, ChinaKey Laboratory of Nondestructive Testing (Ministry of Education), Nanchang Hang Kong University, Nanchang 330031, ChinaSchool of Computing and Digital Technology, Birmingham City University, Birmingham B5 5JU, UKIn infrared small target detection, the infrared patch image (IPI)-model-based methods produce better results than other popular approaches (such as max-mean, top-hat, and human visual system) but in some extreme cases it suffers from long processing times and inconsistent performance. In order to overcome these issues, we propose a novel approach of dividing the traditional target detection process into two steps: suppression of background noise and elimination of clutter. The workflow consists of four steps: after importing the images, the second step applies the alternating direction multiplier method to preliminarily remove the background. Comparatively to the IPI model, this step does not require sliding patches, resulting in a significant reduction in processing time. To eliminate residual noise and clutter, the interim results from morphological filtering are then processed in step 3 through an improved new top-hat transformation, using a threefold structuring element. The final step is thresholding segmentation, which uses an adaptive threshold algorithm. Compared with IPI and the new top-hat methods, as well as some other widely used methods, our approach was able to detect infrared targets more efficiently (90% less computational time) and consistently (no sudden performance drop).https://www.mdpi.com/1424-8220/22/19/7327infrared imagesmall-target detectionalternating direction method of multipliersnew top-hatsignal to clutter ratiobackground suppression factor |
| spellingShingle | Tengyan Xi Lihua Yuan Quanbin Sun A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation Sensors infrared image small-target detection alternating direction method of multipliers new top-hat signal to clutter ratio background suppression factor |
| title | A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation |
| title_full | A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation |
| title_fullStr | A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation |
| title_full_unstemmed | A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation |
| title_short | A Combined Approach to Infrared Small-Target Detection with the Alternating Direction Method of Multipliers and an Improved Top-Hat Transformation |
| title_sort | combined approach to infrared small target detection with the alternating direction method of multipliers and an improved top hat transformation |
| topic | infrared image small-target detection alternating direction method of multipliers new top-hat signal to clutter ratio background suppression factor |
| url | https://www.mdpi.com/1424-8220/22/19/7327 |
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