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Infrared non-uniformity correction algorithm based on classification and regression tree segmentation.

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Title: Infrared non-uniformity correction algorithm based on classification and regression tree segmentation.
Authors: Qu, Wen-qing1,2 (AUTHOR) qwq1996@mail.ustc.edu.cn, Ma, Hao-ran1,2 (AUTHOR) mhara@mail.ustc.edu.cn, Wei, Jiang-yuan1,2 (AUTHOR) pb180206@mail.ustc.edu.cn, Ning, Yu1,2 (AUTHOR) ny7018180@mail.ustc.edu.cn, Li, Jia-ming1,2,3 (AUTHOR) qq1677133500@mail.ustc.edu.cn, Ge, Kun1,2 (AUTHOR) gekun@mail.ustc.edu.cn, Zhang, Hong-fei1,4 (AUTHOR) nghong@ustc.edu.cn, Wang, Jian1,2,3,4 (AUTHOR) wangjian@ustc.edu.cn
Source: Optical Engineering. Jan2025, Vol. 64 Issue 1, p13101-13101. 1p.
Subjects: CART algorithms, Infrared imaging, Infrared detectors, Data integrity, Astronomical observations
Abstract: In infrared imaging, pixel non-uniformity due to manufacturing and technological limitations significantly degrades image quality, posing a critical challenge for high-performance applications. This issue is especially pronounced in the field of infrared astronomical observation, where the scientific integrity of the data must be ensured when correcting infrared images. In addition, the coupling capacitance between pixels leads to nonlinear effects in pixel sensitivity. To address these challenges, a non-uniformity correction (NUC) algorithm was introduced that utilizes classification and regression tree segmentation. This approach enables precise corrections by adapting to varying illuminance levels, a capability not fully explored in existing solutions. In our method, we innovatively segment the pixel response curves into distinct low and high illuminance ranges and apply customized corrections for each segment to enhance the accuracy of correction. Evaluations using real image data demonstrate that our method enhances image quality and consistency. [ABSTRACT FROM AUTHOR]
Copyright of Optical Engineering is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Infrared non-uniformity correction algorithm based on classification and regression tree segmentation.
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  Data: <searchLink fieldCode="AR" term="%22Qu%2C+Wen-qing%22">Qu, Wen-qing</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> qwq1996@mail.ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ma%2C+Hao-ran%22">Ma, Hao-ran</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> mhara@mail.ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wei%2C+Jiang-yuan%22">Wei, Jiang-yuan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> pb180206@mail.ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ning%2C+Yu%22">Ning, Yu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> ny7018180@mail.ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Jia-ming%22">Li, Jia-ming</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> qq1677133500@mail.ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Ge%2C+Kun%22">Ge, Kun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> gekun@mail.ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Hong-fei%22">Zhang, Hong-fei</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<i> nghong@ustc.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Jian%22">Wang, Jian</searchLink><relatesTo>1,2,3,4</relatesTo> (AUTHOR)<i> wangjian@ustc.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Optical+Engineering%22">Optical Engineering</searchLink>. Jan2025, Vol. 64 Issue 1, p13101-13101. 1p.
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  Data: In infrared imaging, pixel non-uniformity due to manufacturing and technological limitations significantly degrades image quality, posing a critical challenge for high-performance applications. This issue is especially pronounced in the field of infrared astronomical observation, where the scientific integrity of the data must be ensured when correcting infrared images. In addition, the coupling capacitance between pixels leads to nonlinear effects in pixel sensitivity. To address these challenges, a non-uniformity correction (NUC) algorithm was introduced that utilizes classification and regression tree segmentation. This approach enables precise corrections by adapting to varying illuminance levels, a capability not fully explored in existing solutions. In our method, we innovatively segment the pixel response curves into distinct low and high illuminance ranges and apply customized corrections for each segment to enhance the accuracy of correction. Evaluations using real image data demonstrate that our method enhances image quality and consistency. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Optical Engineering is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
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      – Type: doi
        Value: 10.1117/1.OE.64.1.013101
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 1
        StartPage: 13101
    Subjects:
      – SubjectFull: CART algorithms
        Type: general
      – SubjectFull: Infrared imaging
        Type: general
      – SubjectFull: Infrared detectors
        Type: general
      – SubjectFull: Data integrity
        Type: general
      – SubjectFull: Astronomical observations
        Type: general
    Titles:
      – TitleFull: Infrared non-uniformity correction algorithm based on classification and regression tree segmentation.
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            NameFull: Qu, Wen-qing
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            NameFull: Ma, Hao-ran
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            NameFull: Wei, Jiang-yuan
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            NameFull: Ning, Yu
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            NameFull: Li, Jia-ming
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            NameFull: Ge, Kun
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            NameFull: Zhang, Hong-fei
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            – D: 01
              M: 01
              Text: Jan2025
              Type: published
              Y: 2025
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              Value: 64
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            – TitleFull: Optical Engineering
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