Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System
The camera response function (CRF) establishes a numerical mapping between focal plane radiance, camera imaging parameters, and the intensity of output images. It plays a significant role in areas such as high dynamic range imaging and image processing. To establish an accurate response model for ti...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10400771/ |
| _version_ | 1797330392114528256 |
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| author | Tan Gao Liangliang Zheng Xiaobin Wu Haolin Ji Biao Yang Wei Xu |
| author_facet | Tan Gao Liangliang Zheng Xiaobin Wu Haolin Ji Biao Yang Wei Xu |
| author_sort | Tan Gao |
| collection | DOAJ |
| description | The camera response function (CRF) establishes a numerical mapping between focal plane radiance, camera imaging parameters, and the intensity of output images. It plays a significant role in areas such as high dynamic range imaging and image processing. To establish an accurate response model for time delay integration (TDI) complementary metal–oxide–semiconductor (CMOS) imaging systems, this article proposes a radiometric calibration method for TDI CMOS imaging systems based on complex real-world scene images. The study begins by conducting an extensive analysis of the data link within the TDI CMOS imaging system, which serves as the foundation for establishing its a priori theoretical response model. Subsequently, the problem of solving the CRF model is transformed into an overdetermined equation established through the least square method. The optimal solution for this equation is obtained by singular value decomposition, which leads to the derivation of a 3-D response function for the imaging system. Finally, under consistent optical radiation conditions, radiation calibration experiments are performed on various targets using a self-developed TDI CMOS imaging system. The CRF is obtained based on the captured experimental image data. Furthermore, this article's approach is compared with the widely adopted linear fitting method commonly used within the respective field. The experimental results show that the visually perceived quality, structural similarity, mean grayscale, mean gradient, entropy, and standard deviation of images synthesized using the CRF proposed in this article are closer to those of actual captured images. The proposed method demonstrates higher accuracy and can provide a reliable basis for applications such as radiation response calibration of on-orbit spaceborne payloads, selection of imaging parameters, and multiexposure fusion of remote sensing images. |
| first_indexed | 2024-03-08T07:19:11Z |
| format | Article |
| id | doaj.art-340c3376bb48400cbdba5fb5a096fc21 |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-03-08T07:19:11Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-340c3376bb48400cbdba5fb5a096fc212024-02-03T00:02:10ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352024-01-01173768377910.1109/JSTARS.2024.335491110400771Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging SystemTan Gao0https://orcid.org/0000-0003-0820-6161Liangliang Zheng1https://orcid.org/0000-0002-0881-0070Xiaobin Wu2https://orcid.org/0000-0003-1860-0920Haolin Ji3https://orcid.org/0009-0002-6035-5308Biao Yang4https://orcid.org/0000-0003-2905-3408Wei Xu5https://orcid.org/0000-0001-6632-3062Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, ChinaThe camera response function (CRF) establishes a numerical mapping between focal plane radiance, camera imaging parameters, and the intensity of output images. It plays a significant role in areas such as high dynamic range imaging and image processing. To establish an accurate response model for time delay integration (TDI) complementary metal–oxide–semiconductor (CMOS) imaging systems, this article proposes a radiometric calibration method for TDI CMOS imaging systems based on complex real-world scene images. The study begins by conducting an extensive analysis of the data link within the TDI CMOS imaging system, which serves as the foundation for establishing its a priori theoretical response model. Subsequently, the problem of solving the CRF model is transformed into an overdetermined equation established through the least square method. The optimal solution for this equation is obtained by singular value decomposition, which leads to the derivation of a 3-D response function for the imaging system. Finally, under consistent optical radiation conditions, radiation calibration experiments are performed on various targets using a self-developed TDI CMOS imaging system. The CRF is obtained based on the captured experimental image data. Furthermore, this article's approach is compared with the widely adopted linear fitting method commonly used within the respective field. The experimental results show that the visually perceived quality, structural similarity, mean grayscale, mean gradient, entropy, and standard deviation of images synthesized using the CRF proposed in this article are closer to those of actual captured images. The proposed method demonstrates higher accuracy and can provide a reliable basis for applications such as radiation response calibration of on-orbit spaceborne payloads, selection of imaging parameters, and multiexposure fusion of remote sensing images.https://ieeexplore.ieee.org/document/10400771/Nonlinearradiometric calibrationresponse functiontime delay integration (TDI) complementary metal–oxide–semiconductor (CMOS) |
| spellingShingle | Tan Gao Liangliang Zheng Xiaobin Wu Haolin Ji Biao Yang Wei Xu Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Nonlinear radiometric calibration response function time delay integration (TDI) complementary metal–oxide–semiconductor (CMOS) |
| title | Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System |
| title_full | Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System |
| title_fullStr | Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System |
| title_full_unstemmed | Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System |
| title_short | Research on Modeling the Nonlinear Response Function of TDI CMOS Imaging System |
| title_sort | research on modeling the nonlinear response function of tdi cmos imaging system |
| topic | Nonlinear radiometric calibration response function time delay integration (TDI) complementary metal–oxide–semiconductor (CMOS) |
| url | https://ieeexplore.ieee.org/document/10400771/ |
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