Infrared and Laser Engineering, Volume. 53, Issue 3, 20240057(2024)

Research progress on polarimetric imaging technology in complex environments based on deep learning (invited)

Haofeng Hu1,2, Yizhao Huang2, Zhen Zhu1, Qianwen Ma1, Jingsheng Zhai1, and Xiaobo Li1、*
Author Affiliations
  • 1School of Marine Science and Technology, Tianjin University, Tianjin 300072, China
  • 2School of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
  • show less
    References(81)

    [1] [1] Goldstein D H. Polarized Light[M]. Boca Raton: CRC Press, 2017.

    [2] [2] Liu X, Zhang L, Zhai X, et al. Polarization lidar: Principles applications[C]Photonics. MDPI, 2023, 10(10): 1118.

    [7] [7] RamellaRoman J C, Novikova T. Polarized Light in Biomedical Imaging Sensing: Clinical Preclinical Applications[M]. Berlin: Springer, 2022.

    [13] C He, H He, J Chang, et al. biomedical and clinical applications: a review. Light: Science & Applications, 10, 194(2021).

    [22] C Zuo, J Qian, S Feng, et al. Deep learning in optical metrology: a review. Light: Science & Applications, 11, 39(2022).

    [24] Haibo Luo, Junchao Zhang, Xingqin Gai, et al. Development status and prospects of polarization imaging technology (Invited). Infrared and Laser Engineering, 51, 20210987(2022).

    [31] [31] Kliger D S, Lewis J W. Polarized Light in Optics Spectroscopy[M]. Amsterdam: Elsevier, 2012.

    [32] Xia Wang, Mingyang Zhang, Zhenyue Chen, et al. Overview on system structure of active polarization imaging. Infrared and Laser Engineering, 42, 2244-2251(2013).

    [38] [38] Li Z, Jiang H, Cao M, et al. Polarized col image denoising [C]2023 IEEECVF Conference on Computer Vision Pattern Recognition (CVPR). IEEE, 2023: 98739882.

    [39] X Xu, M Wan, J Ge, et al. ColorPolarNet: Residual dense network-based chromatic intensity-polarization imaging in low-light environment. IEEE Transactions on Instrumentation and Measurement, 71, 1-10(2022).

    [42] [42] He K, Zhang X, Ren S, et al. Deep residual learning f image recognition[C]Proceedings of the IEEE conference on computer vision pattern recognition, 2016: 770778.

    [43] [43] Huang G, Liu Z, Van Der Maaten L, et al. Densely connected convolutional wks[C]Proceedings of the IEEE conference on computer vision pattern recognition, 2017: 47004708.

    [44] Junhong Song, Zuojiang Xiao, Yingchao Li, et al. Influence of concentration variation of oil mist particles on scattering mueller matrix. Acta Optica Sinica, 41, 2301001(2021).

    [45] Lewei Su, Cunli Duan, Liang Sun et al. Influence of optical polarization on underwater range-gated imaging for target recognition distance under different water quality conditions. Infrared and Laser Engineering, 53, 20230372(2024).

    [48] [48] Chen C, Chen Q, Xu J, et al. Learning to see in the dark[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2018: 32913300.

    [49] C Zhou, M Teng, Y Han, et al. Learning to dehaze with polarization. Advances in Neural Information Processing Systems, 34, 11487-11500(2021).

    [50] H Zhao, O Gallo, I Frosio, et al. Loss functions for image restoration with neural networks. IEEE Transactions on Computational Imaging, 3, 47-57(2016).

    [52] [52] Johnson J, Alahi A, FeiFei L. Perceptual losses f realtime style transfer superresolution [C]Computer Vision–ECCV 2016: 14th European Conference, 2016: 694711.

    [54] [54] Agaian S S, Pata K, Grigyan A M. A new measure of image enhancement [C]IASTED International Conference on Signal Processing & Communication, 2000: 1922.

    [55] Y Xiang, X Yang, Q Ren, et al. Underwater polarization imaging recovery based on polarimetric residual dense network. IEEE Photonics Journal, 14, 1-6(2022).

    [57] D Li, B Lin, X Wang, et al. High-performance polarization remote sensing with the modified U-net based deep-learning network. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-10(2022).

    [58] [58] Almahairi A, Rajeshwar S, Sdoni A, et al. Augmented cyclegan: Learning manytomany mappings from unpaired data [C]International Conference on Machine Learning, PMLR, 2018: 195204.

    [59] [59] Zhu J Y, Park T, Isola P, et al. Unpaired imagetoimage translation using cycleconsistent adversarial wks [C]Proceedings of the IEEE International Conference on Computer Vision, 2017: 22232232.

    [61] B Zoph, G Ghiasi, T Y Lin, et al. Rethinking pre-training and self-training. Advances in Neural Information Processing Systems, 33, 3833-3845(2020).

    [68] [68] Li S, Ye W, Liang H, et al. KSVD based denoising algithm f DoFP polarization image senss [C]2018 IEEE International Symposium on Circuits Systems (ISCAS). IEEE, 2018: 15.

    [69] [69] Buades A, Coll B, Mel J M. A nonlocal algithm f image denoising [C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2005: 6065.

    [75] [75] Yosinski J, Clune J, Bengio Y, et al. Advances in neural infmation processing systems [C]Proceedings of the 27th International Conference on Neural Infmation Processing Systems, 2014: 3320–3328.

    [76] H Hu, H Jin, H Liu, et al. Polarimetric image denoising on small datasets using deep transfer learning. Optics & Laser Technology, 166, 109632(2023).

    [77] Haofeng Hu, Huifeng Jin, Xiaobo Li, et al. Polarization image denoising based on unsupervised learning. Acta Optica Sinica, 43, 0410001(2023).

    [78] J Lehtinen, J Munkberg, J Hasselgren, et al. Noise2Noise: Learning image restoration without clean data.

    [81] H Liu, X Li, Z Cheng, et al. Polarization maintaining 3-D convolutional neural network for color polarimetric images denoising. IEEE Transactions on Instrumentation and Measurement, 72, 1-9(2023).

    Tools

    Get Citation

    Copy Citation Text

    Haofeng Hu, Yizhao Huang, Zhen Zhu, Qianwen Ma, Jingsheng Zhai, Xiaobo Li. Research progress on polarimetric imaging technology in complex environments based on deep learning (invited)[J]. Infrared and Laser Engineering, 2024, 53(3): 20240057

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Jan. 31, 2024

    Accepted: --

    Published Online: Jun. 21, 2024

    The Author Email: Li Xiaobo (lixiaobo@tju.edu.cn)

    DOI:10.3788/IRLA20240057

    Topics