Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure

Infrared small target detection plays a crucial role in fields such as remote sensing and surveillance. However, during long-distance imaging, factors such as atmospheric attenuation lead to a low signal-to-clutter ratio for the targets, making their features difficult to extract effectively. Additi...

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Main Authors: Yuyang Xi, Yushan Zhang, Ying Jiang, Liuwei Zhang, Qingyu Hou
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Remote Sensing
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Online Access:https://www.mdpi.com/2072-4292/17/8/1442
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author Yuyang Xi
Yushan Zhang
Ying Jiang
Liuwei Zhang
Qingyu Hou
author_facet Yuyang Xi
Yushan Zhang
Ying Jiang
Liuwei Zhang
Qingyu Hou
author_sort Yuyang Xi
collection DOAJ
description Infrared small target detection plays a crucial role in fields such as remote sensing and surveillance. However, during long-distance imaging, factors such as atmospheric attenuation lead to a low signal-to-clutter ratio for the targets, making their features difficult to extract effectively. Additionally, in complex background environments, background components that resemble the target morphology highly interfere with detection tasks. Therefore, infrared weak small target detection in complex backgrounds faces challenges of low detection accuracy and high false alarm rates. To solve the above difficulties, a novel entropy variation weighted local contrast measure (EVWLCM) is proposed. Firstly, a target saliency enhancement method based on a family of generalized Gaussian functions is introduced, which accurately characterizes the grayscale distribution states of various targets in infrared images. Secondly, a novel adaptive weighting strategy based on local joint entropy variation characteristics is suggested. Specifically, the spatial grayscale distribution difference between the target and the background is effectively perceived, enhancing the target while suppressing the background. Finally, experimental results on real infrared images show that EVWLCM outperforms existing methods on both public and private datasets. Additionally, the average processing speed of EVWLCM is 34 frames per second, which meets the requirements for real-time scenarios.
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institution DOAJ
issn 2072-4292
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publishDate 2025-04-01
publisher MDPI AG
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spelling doaj-art-614bc1e23bf748e9838dc9884df0155f2025-08-20T03:13:32ZengMDPI AGRemote Sensing2072-42922025-04-01178144210.3390/rs17081442Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast MeasureYuyang Xi0Yushan Zhang1Ying Jiang2Liuwei Zhang3Qingyu Hou4The Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaShanghai Institute of Satellite Engineering, Shanghai 201109, ChinaThe Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaThe Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaThe Research Center for Space Optical Engineering, Harbin Institute of Technology, Harbin 150001, ChinaInfrared small target detection plays a crucial role in fields such as remote sensing and surveillance. However, during long-distance imaging, factors such as atmospheric attenuation lead to a low signal-to-clutter ratio for the targets, making their features difficult to extract effectively. Additionally, in complex background environments, background components that resemble the target morphology highly interfere with detection tasks. Therefore, infrared weak small target detection in complex backgrounds faces challenges of low detection accuracy and high false alarm rates. To solve the above difficulties, a novel entropy variation weighted local contrast measure (EVWLCM) is proposed. Firstly, a target saliency enhancement method based on a family of generalized Gaussian functions is introduced, which accurately characterizes the grayscale distribution states of various targets in infrared images. Secondly, a novel adaptive weighting strategy based on local joint entropy variation characteristics is suggested. Specifically, the spatial grayscale distribution difference between the target and the background is effectively perceived, enhancing the target while suppressing the background. Finally, experimental results on real infrared images show that EVWLCM outperforms existing methods on both public and private datasets. Additionally, the average processing speed of EVWLCM is 34 frames per second, which meets the requirements for real-time scenarios.https://www.mdpi.com/2072-4292/17/8/1442infrared small target detectionlocal contrast measuregeneralized Gaussian function familylocal joint entropy variation characteristics
spellingShingle Yuyang Xi
Yushan Zhang
Ying Jiang
Liuwei Zhang
Qingyu Hou
Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure
Remote Sensing
infrared small target detection
local contrast measure
generalized Gaussian function family
local joint entropy variation characteristics
title Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure
title_full Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure
title_fullStr Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure
title_full_unstemmed Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure
title_short Infrared Small Target Detection Based on Entropy Variation Weighted Local Contrast Measure
title_sort infrared small target detection based on entropy variation weighted local contrast measure
topic infrared small target detection
local contrast measure
generalized Gaussian function family
local joint entropy variation characteristics
url https://www.mdpi.com/2072-4292/17/8/1442
work_keys_str_mv AT yuyangxi infraredsmalltargetdetectionbasedonentropyvariationweightedlocalcontrastmeasure
AT yushanzhang infraredsmalltargetdetectionbasedonentropyvariationweightedlocalcontrastmeasure
AT yingjiang infraredsmalltargetdetectionbasedonentropyvariationweightedlocalcontrastmeasure
AT liuweizhang infraredsmalltargetdetectionbasedonentropyvariationweightedlocalcontrastmeasure
AT qingyuhou infraredsmalltargetdetectionbasedonentropyvariationweightedlocalcontrastmeasure