Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity
Infrared maritime target detection is a key technology in the field of maritime search and rescue, which usually requires high detection accuracy. Despite the promising progress of principal component analysis methods, it is still challenging to detect small targets of unknown polarity (bright or da...
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MDPI AG
2022-10-01
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Online Access: | https://www.mdpi.com/2072-4292/14/21/5492 |
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author | Enzhong Zhao Lili Dong Hao Dai |
author_facet | Enzhong Zhao Lili Dong Hao Dai |
author_sort | Enzhong Zhao |
collection | DOAJ |
description | Infrared maritime target detection is a key technology in the field of maritime search and rescue, which usually requires high detection accuracy. Despite the promising progress of principal component analysis methods, it is still challenging to detect small targets of unknown polarity (bright or dark) with strong edge interference. Using the partial sum of tubal nuclear norm to estimate low-rank background components and weighted <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>l</mi><mn>1</mn></msub></semantics></math></inline-formula> norm to estimate sparse components is an effective method for target extraction. In order to suppress the strong edge interference, considering that the uniformity of the target scattering field is significantly higher than that of the background scattering field in the eigenvalue of the structure tensor, a prior weight based on the multidirectional uniformity of structure tensor eigenvalue was proposed and applied to the optimization model. In order to detect targets with unknown polarity, the images with opposite polarity were substituted into the optimization model, respectively, and the sparse-weight similarity is used to judge the polarity of the target. In order to make the method more efficient, the polarity judgment is made in the second iteration, and then, the false iteration will stop. The proposed method is compared with nine advanced baseline methods on 14 datasets and shows significant strong robustness, which is beneficial to engineering applications. |
first_indexed | 2024-03-09T18:42:00Z |
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id | doaj.art-62d28eb2e54d499aae90d85490cc6e07 |
institution | Directory Open Access Journal |
issn | 2072-4292 |
language | English |
last_indexed | 2024-03-09T18:42:00Z |
publishDate | 2022-10-01 |
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series | Remote Sensing |
spelling | doaj.art-62d28eb2e54d499aae90d85490cc6e072023-11-24T06:39:54ZengMDPI AGRemote Sensing2072-42922022-10-011421549210.3390/rs14215492Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight SimilarityEnzhong Zhao0Lili Dong1Hao Dai2School of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaInfrared maritime target detection is a key technology in the field of maritime search and rescue, which usually requires high detection accuracy. Despite the promising progress of principal component analysis methods, it is still challenging to detect small targets of unknown polarity (bright or dark) with strong edge interference. Using the partial sum of tubal nuclear norm to estimate low-rank background components and weighted <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>l</mi><mn>1</mn></msub></semantics></math></inline-formula> norm to estimate sparse components is an effective method for target extraction. In order to suppress the strong edge interference, considering that the uniformity of the target scattering field is significantly higher than that of the background scattering field in the eigenvalue of the structure tensor, a prior weight based on the multidirectional uniformity of structure tensor eigenvalue was proposed and applied to the optimization model. In order to detect targets with unknown polarity, the images with opposite polarity were substituted into the optimization model, respectively, and the sparse-weight similarity is used to judge the polarity of the target. In order to make the method more efficient, the polarity judgment is made in the second iteration, and then, the false iteration will stop. The proposed method is compared with nine advanced baseline methods on 14 datasets and shows significant strong robustness, which is beneficial to engineering applications.https://www.mdpi.com/2072-4292/14/21/5492infrared maritime small target detectionmultidirectional uniformitypartial sum of the tubal nuclear normtarget polarity judgmentsparse-weight similarity |
spellingShingle | Enzhong Zhao Lili Dong Hao Dai Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity Remote Sensing infrared maritime small target detection multidirectional uniformity partial sum of the tubal nuclear norm target polarity judgment sparse-weight similarity |
title | Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity |
title_full | Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity |
title_fullStr | Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity |
title_full_unstemmed | Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity |
title_short | Infrared Maritime Small Target Detection Based on Multidirectional Uniformity and Sparse-Weight Similarity |
title_sort | infrared maritime small target detection based on multidirectional uniformity and sparse weight similarity |
topic | infrared maritime small target detection multidirectional uniformity partial sum of the tubal nuclear norm target polarity judgment sparse-weight similarity |
url | https://www.mdpi.com/2072-4292/14/21/5492 |
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