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Research Article

Single-frame remote sensing image defogging network based on attention residual blocks and contrast learning

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Pages 4346-4371 | Received 05 Apr 2023, Accepted 27 Jun 2023, Published online: 24 Jul 2023

References

  • Ancuti, C. O., C. Ancuti, Vleeschouwer, C. De. 2018. “Effective Local Airlight Estimation for Image Dehazing.“ In 2018 25th IEEE International Conference on Image Processing (ICIP), Athens, Greece, 2850–2854. https://doi.org/10.1109/ICIP.2018.8451523.
  • Anderson, K., B. Ryan, W. Sonntag, A. Kavvada, and L. Friedl. 2017. “Earth Observation in Service of the 2030 Agenda for Sustainable Development.” Geo-Spatial Information Science 20 (2): 77–96. https://doi.org/10.1080/10095020.2017.1333230.
  • Berman, D., S. Avidan, Treibitz, T., et al. 2016. “Non-Local Image Dehazing.“ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 1674–1682.
  • Chen, D., M. He, Q. Fan, Liao, Jing ,Zhang, Liheng, Hou, Dongdong, Yuan, Lu ,Hua, “Gang. 2019 Gated context aggregation network for image dehazing and deraining[C]”. 2019 IEEE winter conference on applications of computer vision (WACV). IEEE. 1375–1383.
  • Chen, T., S. Kornblith, and G.-O. Hinton. 2020. “A Simple Framework for Contrastive Learning of Visual Representations.“ Proceeding of the 37th International Conference on Machine Learning 2 (3): 5. arXiv preprint arXiv:2002.05709.
  • Choi, L. K., J. You, and A. C. Bovik. 2015. “Referenceless Prediction of Perceptual Fog Density and Perceptual Image Defogging.” IEEE Transactions on Image Processing 24 (11): 3888–3901. https://doi.org/10.1109/TIP.2015.2456502.
  • Dai, S., W. Xu, Y. Pu, and Y. Chen. 2017. “Remote Sensing Image Defogging Method Based on DCP.” GuangxueXuebao/Acta Optica Sinica 37:348–354.
  • Destek, M. A., and S. A. Sarkodie. 2019. “Investigation of Environmental Kuznets Curve for Ecological Footprint: The Role of Energy and Financial Development.” Science of the Total Environment 650:2483–2489. https://doi.org/10.1016/j.scitotenv.2018.10.017.
  • Du, Y., B. Guindon, and J. Cihlar. 2002. “Haze Detection and Removal in High Resolution Satellite Image with Wavelet Analysis.” IEEE Transactions on Geoscience and Remote Sensing: A Publication of the IEEE Geoscience and Remote Sensing Society 40 (1): 210–217. https://doi.org/10.1109/36.981363.
  • Duta I. C., L. Liu, Shao L. 2021. “Improved Residual Networks for Image and Video Recognition.” In 25th International Conference on Pattern Recognition (ICPR), Milan, Italy. 9415–9422. https://doi.org/10.1109/ICPR48806.2021.9412193.
  • Engin D., A. Geng, and H. Kemal Ekenel. 2018. “Cycle-dehaze: Enhanced cyclegan for single image dehazing.“ In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Utah, Salt Lake City, 825–833.
  • Rourke ML, Fowler AM, Hughes JM, Broadhurst MK, DiBattista JD, Fielder S, Wilkes Walburn J, et al. 2022. “Environmental DNA (eDNA) as a Tool for Assessing Fish Biomass: A Review of Approaches and Future Considerations for Resource Surveys.” Environmental DNA 4 (1): 9–33. https://doi.org/10.1002/edn3.185.
  • Hénaff, O. J., A. Srinivas, J. De Fauw, A. Razavi, C. Doersch, SM Eslami, and Aaron van den Oord.Data-Efficient Image Recognition with Contrastive Predictive Coding. arXiv preprint arXiv:1905.09272, 2019.3
  • He, N., L. Shao, J. Xue, N. He, and L. Shao. 2017. “Single Image Dehazing Based on the Physical Model andMsrcr Algorithm. IEEE T Rans.Circuits Syst. Video T Echnol.” IEEE Transactions on Circuits and Systems for Video Technology 28 (9): 2190–2199. https://doi.org/10.1109/TCSVT.2017.2728822. CrossRef.
  • He, K., J. Sun, and X. Tang. 2010. “Single Image Haze Removal Using Dark Channel Prior.” IEEE Transactions on Pattern Analysis & Machine Intelligence 33 (12): 2341–2353. https://doi.org/10.1109/TPAMI.2010.168.
  • Huang, S., Y. Liu, Y. Wang, Z. Wang, and J. Guo. 2020. “A New Haze Removal Algorithm for Single Urban Remote Sensing Image.” IEEE Access 8 (1): CrossRef. https://doi.org/10.1109/ACCESS.2020.2997985.
  • Huang, P., L. Zhao, R. Jiang, T. Wang, and X. Zhang. 2021. “Self-Filtering Image Dehazing with Self-Supporting Module.” Neurocomputing 2021 432:57–69. CrossRef. https://doi.org/10.1016/j.neucom.2020.11.039.
  • Huynh-Thu, Q., and M. Ghanbari. 2008. “Scope of Validity of PSNR in Image/Video Quality Assessment.” Electronics Letters 44 (13): 800–801. https://doi.org/10.1049/el:20080522.
  • Ju, Mingye, Chuheng Chen, Liu, Juping, Chen, Kai, Zhang, Dengyin. 2021. “VRHI: Visibility Restoration for Hazy Images Using a Hazedensity Model.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Patterm Recognition, (CVPR) Workshops Canada, Montreal. 897–904.
  • Ju, M., D. Zhang, and X. Wang. 2017. “Single Image Dehazing via an Improved Atmospheric Scattering Model. Vis.” Comput 33 (12): 1613–1625. https://doi.org/10.1007/s00371-016-1305-1. CrossRef.
  • Kaiming, H., and H. Fan. 2, 2020. “Y Uxin Wu, Saining Xie. Momentum Contrast for Unsupervised Visual Rep-Resentation Learning.” CVPR 3 (5): 9729–9738.
  • Kim, J.-Y., L.-S. Kim, and S.-H. Hwang. 2001. “An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization.” IEEE Transactions on Circuits and Systems for Video Technology 11 (4): 475–484. https://doi.org/10.1109/76.915354. CrossRef.
  • Kim, T. K., J. Paik, and B. S. Kang. 1998. “Contrast Enhancement System Using Spatially Adaptive Histogram Equalization with Temporal Filtering.” IEEE Transactions on Consumer Electronics 44 (1): 82–87. https://doi.org/10.1109/30.663733. CrossRef.
  • Land, E. H. Land, and J. J. McCann. 1971. “E.Lightness and Retinex Theory.” Journal of the Optical Society of America 61 (1): 1–11. https://doi.org/10.1364/JOSA.61.000001. [CrossRef] [PubMed].
  • Li, B.; X. Peng; Z. Wang; J. Xu; D. Feng AOD-Net: All-In-One Dehazing Network. In Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), V enice, Italy, 22–29 October 2017b; pp. 4780–4788.
  • Li, B., X. Peng, Z. Wang, J. Xu and D. Feng, “AOD-Net: All-In-One Dehazing Network,” 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy, 2017a, pp. 4780–4788, https://doi.org/10.1109/ICCV.2017.511.
  • Long, J., Z. Shi, W. Tang, and C. Zhang. 2013. “Single Remote Sensing Image Dehazing.” IEEE Geoscience & Remote Sensing Letters 11 (1): 59–63. https://doi.org/10.1109/LGRS.2013.2245857. CrossRef.
  • Luo, H.-L., and J.-B. Lin. 2013. “A Multi-Scale Retinex Algorithm-Based Image Defogging Method.” Computer Applications and Software 30 (4): 58–60+127.
  • Mittal, A., R. Soundararajan, and A. C. Bovik. 2012. “Making a “Completely blind” Image Quality Analyzer.” IEEE Signal Processing Letters 20 (3): 209–212. https://doi.org/10.1109/LSP.2012.2227726.
  • Munawar, H. S., A. W. A. Hammad, and S. T. Waller. 2022. “Remote Sensing Methods for Flood Prediction: A Review.” Sensors 200 (3): 960. https://doi.org/10.3390/s22030960.
  • Park, T., AA. Efros, R. Zhang, and JY. Zhu. 2020. “Contrastive Learning for Unpaired Image-To-Image Translation.“ Computer Vision - ECCV 2020 12354. arXiv preprint arXiv:2007.15651. https://doi.org/10.1109/ICPR48806.2021.9412193.
  • Qin, X., Z. Wang, Y. Bai. 2020. “FFA-Net: Feature fusion attention netwccork for single image dehazing[C].“ In Proceedings of the AAAI conference on artificial intelligence, Hilton New York Midtown. 34( 07): 11908–11915.
  • Qi, Wang, Wang Shigang, Jia Bowen, Hailong, Du. 2018. “Curvelet Transform and Contrast Adaptive Clip Histogram Equalization-Based Image Defogging Algorithm.” The Journal of China Universities of Posts and Telecommunications 5 (2): 100–108.
  • Ren, Wenqi, Lin Ma, Jiawei Zhang, Pan, Jinshan, Cao, xiaochun, Yang, Ming-Hsuan. 2018. “Gated Fusion Network for Single Image Dehazing[cj.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition], Utah, Salt Lake City. 3253–3261.
  • Sandler, Mark, Andrew Howard, Menglong Zhu, Zhmoginov, Andrey, Chen, Liang-Chieh. 2018. “Mobilenetv2: Inverted residuals and linear bottlenecks[C].“ Proceedings of the IEEE conference on computer vision and pattern recognition, Utah, Salt Lake City. 4510–4520.
  • Shen, H., H. Li, Y. Qian, L. Zhang, and Q. Yuan. 2014. “An Effective Thin Cloud Removal Procedure for Visible Remote Sensing Images.” Isprs Journal of Photogrammetry & Remote Sensing 96:224–235. https://doi.org/10.1016/j.isprsjprs.2014.06.011.
  • Shi, W., and J. Li. 2010. “Research on Remote Sensing Image Dehazing Algorithm. Spacecr.” Recovery Remote Sens 31 (6): 46–51.
  • Simonyan, K. and A. Zisserman. Very Deep Convolutional Networks for Large-Scale Image Recognition. arXiv preprint arXiv:1409.1556, 2014. 5
  • Ullah, H., K. Muhammad, M. Irfan, S. Anwar, M. Sajjad, A. S. Imran, and V. H. C. de Albuquerque. 2021. “Light-DehazeNet: A Novel Lightweight CNN Architecture for Single Image Dehazing.” IEEE Transactions on Image Processing 30:8968–8982. https://doi.org/10.1109/TIP.2021.3116790.
  • Wang, Z., A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. 2004. “Simoncelli: Image Quality Assessment: From Error Visibility to Structural Similarity.” IEEE Transactions on Image Processing 13 (4): 600–612. https://doi.org/10.1109/TIP.2003.819861.
  • Wang, L., J. Xie, and W. Pei. 2015. “Patch-Based Dark Channel Prior Dehazing for RS Multi-Spectral Image.” Chinese Journal of Electronics 24 (3): 573–578. https://doi.org/10.1049/cje.2015.07.023. CrossRef.
  • Xiaohong Liu, Y. O. M., Z. Shi, and J. Chen. 2019. GridDehazenet: Attention-Based Multi-Scale Network for Image Dehazing. In ICCV 1, 2, 3, 4, 5, 6, 7, 8
  • Xiaojun, Z., G. Jia, and Z. Chengxian. 2015. “Remote Sensing Image de-Clouding Algorithm Based on Improved Homomorphic Filtering.” Radio Engineering 45 (3): 14–18.
  • Xie, F., J. Chen, X. Pan, and Z. Jiang. 2018. “Adaptive Haze Removal for Single Remote Sensing Image.” IEEE Access 6:67982–67991. CrossRef. https://doi.org/10.1109/ACCESS.2018.2879893.
  • Zhan, J.; Y. Gao; X. Liu Measuring the Optical Scattering Characteristics of Large Particles in Visible Remote Sensing. In Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA, 23–28 July 2017;pp. 4666–4669.
  • Zhang, H.; V. M. Patel Densely Connected Pyramid Dehazing Network. In Proceedings of the 2018 IEEE/CVF Conference on Utah, Salt Lake City.
  • Zhao, X.2021. “Single Image Dehazing Using Bounded Channel Difference Prior.” Proceedings of the Conference on Computer Vision and Pattern Recognition, Virtual. 727–735.
  • Zhongming, Zhao, Chongguang, Zhu.1996. “Zhu Chongguang. A Method for Removing Thin Clouds from Remote Sensing Images.” Environmental Remote Sensing, no. 3:195–199.
  • Zhu, Q., J. Mai, and L. Shao. 2015. “A Fast Single Image Haze Removal Algo-Rithm Using Color Attenuation Prior.” IEEE Transactions on Image Processing 24 (11): 3522–3533. https://doi.org/10.1109/TIP.2015.2446191.
  • Zindel, R., Y. Gottlieb, and A. Aebi. 2011. “Arthropod Symbioses: A Neglected Parameter in Pest‐And Disease‐Control Programmes.” Journal of Applied Ecology 48 (4): 864–872. https://doi.org/10.1111/j.1365-2664.2011.01984.x.

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