| 计算机技术、通信技术 |
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| 基于不变学习的真实雾霾去除方法 |
孟小哲( ),冯钰新,苏卓*(),周凡 |
| 中山大学 计算机学院，中山大学深圳研究院，广东 广州 510000 |
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| Real-world dehazing method with invariant learning |
| Xiaozhe MENG(),Yuxin FENG,Zhuo SU*(),Fan ZHOU |
| School of Computer Science and Engineering, Research Institute of Sun Yat-sen University in Shenzhen, Sun Yat-sen University, Guangzhou 510000, China |
引用本文:
孟小哲,冯钰新,苏卓,周凡. 基于不变学习的真实雾霾去除方法[J]. 浙江大学学报(工学版), 2024, 58(2): 268-278.
Xiaozhe MENG,Yuxin FENG,Zhuo SU,Fan ZHOU. Real-world dehazing method with invariant learning. Journal of ZheJiang University (Engineering Science), 2024, 58(2): 268-278.
链接本文:
https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2024.02.005
或
https://www.zjujournals.com/eng/CN/Y2024/V58/I2/268
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| 1 |
ARYAN M, MURARI M, PRATIK N, et al ReViewNet: a fast and resource optimized network for enabling safe autonomous driving in hazy weather conditions[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 22: 4256- 4266
doi: 10.1109/TITS.2020.3013099
|
| 2 |
CAO Z, QIN Y, JIA L, et al Haze removal of railway monitoring images using multi-scale residual network[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22 (12): 7460- 7473
|
| 3 |
BAI H, PAN J, XIANG X, et al Self-guided image dehazing using progressive feature fusion[J]. IEEE Transactions on Image Processing, 2022, 31: 1217- 1229
doi: 10.1109/TIP.2022.3140609
|
| 4 |
WU H, QU Y, LIN S, et al. Contrastive learning for compact single image dehazing [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . [S. l. ]: IEEE, 2021: 10551-10560.
|
| 5 |
LI H, LI J, ZHAO D, et al. Dehazeflow: multi-scale conditional flow network for single image dehazing [C]// Proceedings of the 29th ACM International Conference on Multimedia . New York: ACM, 2021: 2577-2585.
|
| 6 |
QIN X, WANG Z, BAI Y, et al. FFA-Net: feature fusion attention network for single image dehazing [C]// Proceedings of the AAAI Conference on Artificial Intelligence . New York: AAAI, 2020: 11908-11915.
|
| 7 |
MA L, MA T, LIU R, et al. Toward fast, flexible, and robust low-light image enhancement [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . New Orleans: IEEE, 2022: 5637-5646.
|
| 8 |
ARJOVSKY M, BOTTOU L, GULRAJANI I, et al. Invariant risk minimization [EB/OL]. (2019-07-05). https://arxiv.org/pdf/1907.02893.pdf.
|
| 9 |
WANG J, LAN C, LIU C, et al Generalizing to unseen domains: a survey on domain generalization[J]. IEEE Transactions on Knowledge and Data Engineering, 2023, 35 (8): 8052- 8072
|
| 10 |
MUANDET K, BALDUZZI D, SCHÖLKOPF B. Domain generalization via invariant feature representation [C]/ /International Conference on Machine Learning . Atlanta: ACM, 2013: 10-18.
|
| 11 |
KUANG K, CUI P, ATHEY S, et al. Stable prediction across unknown environments [C]// Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . London: ACM, 2018: 1617-1626.
|
| 12 |
KUANG K, XIONG R, CUI P, et al. Stable prediction with model misspecification and agnostic distribution shift [C]// Proceedings of the AAAI Conference on Artificial Intelligence . New York: AAAI, 2020: 4485-4492.
|
| 13 |
ZHANG X, CUI P, XU R, et al. Deep stable learning for out-of-distribution generalization [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition .[S. l. ]: IEEE, 2021: 5372-5382.
|
| 14 |
HE K, SUN J, TANG X Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 33 (12): 2341- 2353
|
| 15 |
FATTAL R Dehazing using color-lines[J]. ACM Transactions on Graphics, 2014, 34 (1): 1- 14
|
| 16 |
BERMAN D, AVIDAN S. Non-local image dehazing [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . Las Vegas: IEEE, 2016: 1674-1682.
|
| 17 |
LI B, REN W, FU D, et al Benchmarking single-image dehazing and beyond[J]. IEEE Transactions on Image Processing, 2018, 28 (1): 492- 505
|
| 18 |
LIU X, MA Y, SHI Z, et al. Griddehazenet: attention-based multi-scale network for image dehazing [C]// Proceedings of the IEEE/CVF International Conference on Computer Vision . Montreal: IEEE, 2019: 7314-7323.
|
| 19 |
DONG H, PAN J, XIANG L, et al. Multi-scale boosted dehazing network with dense feature fusion [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . Seattle: IEEE, 2020: 2157-2167.
|
| 20 |
KIM G, KWON J Deep illumination-aware dehazing with low-light and detail enhancement[J]. IEEE Transactions on Intelligent Transportation Systems, 2021, 23 (3): 2494- 2508
|
| 21 |
JU M, DING C, REN W, et al IDE: image dehazing and exposure using an enhanced atmospheric scattering model[J]. IEEE Transactions on Image Processing, 2021, 30: 2180- 2192
doi: 10.1109/TIP.2021.3050643
|
| 22 |
CHEN Z, WANG Y, YANG Y, et al. PSD: principled synthetic-to-real dehazing guided by physical priors [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . [S. l. ]: IEEE, 2021: 7180-7189.
|
| 23 |
SHAO Y, LI L, REN W, et al. Domain adaptation for image dehazing [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . Seattle: IEEE, 2020: 2808-2817.
|
| 24 |
LIANG Y, WANG B, ZUO W, et al. Self-supervised learning and adaptation for single image dehazing [C]// Proceedings of the 31st International Joint Conference on Artificial Intelligence . Vienna: Morgan Kaufmann, 2022: 1-15.
|
| 25 |
LI R, PAN J, LI Z, et al. Single image dehazing via conditional generative adversarial network [C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . Salt Lake City: IEEE, 2018: 8202-8211.
|
| 26 |
NARASIMHAN S G, NAYAR S K Vision and the atmosphere[J]. International Journal of Computer Vision, 2002, 48 (3): 233
doi: 10.1023/A:1016328200723
|
| 27 |
YANG W, WANG W, HUANG H, et al Sparse gradient regularized deep Retinex network for robust low-light image enhancement[J]. IEEE Transactions on Image Processing, 2021, 30: 2072- 2086
doi: 10.1109/TIP.2021.3050850
|
| 28 |
ZEILER M D, FERGUS R. Visualizing and understanding convolutional networks [C]// European Conference Computer Vision . Zurich: Springer, 2014: 818-833.
|
| 29 |
GRAY R M, GOODMAN J W. Fourier transforms: an introduction for engineers [M]. Berlin: Springer, 2012: 53-113.
|
| 30 |
LI L, DONG Y, REN W, et al Semi-supervised image dehazing[J]. IEEE Transactions on Image Processing, 2019, 29: 2766- 2779
|
| 31 |
YANG Y, WANG C, LIU R, et al. Self-augmented unpaired image dehazing via density and depth decomposition [C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . New Orleans: IEEE, 2022: 2037-2046.
|
| 32 |
GU K, TAO D, QIAO J F, et al Learning a no-reference quality assessment model of enhanced images with big data[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 29 (4): 1301- 1313
|
| 33 |
GU K, QIAO J, LI X Highly efficient picture-based prediction of PM2.5 concentration[J]. IEEE Transactions on Industrial Electronics, 2018, 66 (4): 3176- 3184
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