| Citation: | LI Y H，YU H K，MA D F，et al. Improved transfer learning based dual-branch convolutional neural network image dehazing[J]. Journal of Beijing University of Aeronautics and Astronautics，2024，50（1）：30-38 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0253
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To address the problems of incomplete dehazing and image color distortion in the existing image dehazing algorithms, a dehazing network combining transfer learning sub-net and residual attention sub-net is proposed. First, the pre-trained model of the transfer learning subnet is adopted to enhance the feature attributes of the samples. Second, the structure of the dual-branch network is constructed, and the residual attention sub-network is used to assist the transfer learning sub-network to train the parameters of the network model. Finally, the method of tail ensemble learning is used to fuse the features of the dual network to obtain the model parameters of the dehazed image, so as to complete the image restoration task.The experimental results show that the algorithm proposed in the paper improves the PSNR index by 1.87 dB and 4.22 dB on the RESIDE dataset and the O-HAZE dataset respectively compared to GCANet, and the SSIM index on the O-HAZE dataset by 6.7% compared to GCANet.
| [1] |
禹晶, 徐东彬, 廖庆敏. 图像去雾技术研究进展[J]. 中国图象图形学报, 2011, 16(9): 1561-1576.
YU J, XU D B, LIAO Q M. Imagedefogging: A survey[J]. Journal of Image and Graphics, 2011, 16(9): 1561-1576(in Chinese).
|
| [2] |
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.
|
| [3] |
ZHU Q, MAI J, SHAO L. A fast single image haze removal algorithm using color attenuation prior[J]. IEEE Transactions on Image Processing, 2015, 24(11): 3522-3533. doi: 10.1109/TIP.2015.2446191
|
| [4] |
TAN R T. Visibility in bad weather from a single image[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE Press, 2008: 1-8.
|
| [5] |
杨燕, 张金龙, 张浩文. 基于区间估计与透射率自适应约束的去雾算法[J]. 北京航空航天大学学报, 2022, 48(1): 15-26. doi: 10.13700/j.bh.1001-5965.2020.0547
YANG Y, ZHANG J L, ZHANG H W. Dehazing algorithm based on interval estimation and adaptive constraints of transmittance[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(1): 15-26(in Chinese). doi: 10.13700/j.bh.1001-5965.2020.0547
|
| [6] |
CAI B, XU X, JIA K, et al. DehazeNet: An end-to-end system for single image haze removal[J]. IEEE Transactions on Image Processing, 2016, 25(11): 5187-5198. doi: 10.1109/TIP.2016.2598681
|
| [7] |
REN W, LIU S, ZHANG H, et al. Single image dehazing via multi-scale convolutional neural networks[C]//Proceedings of the European conference on Computer Vision. Berlin: Springer, 2016: 154-169.
|
| [8] |
LI B, PENG X, WANG Z, et al. AOD-Net: All-in-one dehazing network[C]//Proceedings of the IEEE International Conference on Computer Vision. Piscataway: IEEE Press, 2017: 4770-4778.
|
| [9] |
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. Piscataway: IEEE Press, 2019: 7314-7323.
|
| [10] |
CHEN D, HE M, FAN Q, et al. Gated context aggregation network for image dehazing and deraining[C]//Proceedings of the IEEE Winter Conference on Applications of Computer Vision. Piscataway: IEEE Press, 2019: 1375-1383.
|
| [11] |
王殿伟, 李顺利, 韩鹏飞. 基于特征约束CycleGAN的单幅图像去雾算法研究[J]. 激光与光电子学进展, 2021, 58(14): 272-278.
WANG D W, LI S L, HANG P F. Feature constraint CycleGAN for single image dehazing algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(14): 272-278(in Chinese).
|
| [12] |
HE K, ZHANG X, REN S, et al. Deep residual learning for image recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE Press, 2016: 770-778.
|
| [13] |
NIU Z, ZHONG G, YU H. A review on the attention mechanism of deep learning[J]. Neurocomputing, 2021, 452: 48-62. doi: 10.1016/j.neucom.2021.03.091
|
| [14] |
ZHU J Y, PARK T, ISOLA P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks[C]//Proceedings of the IEEE International Conference on Computer Vision. Piscataway: IEEE Press, 2017: 2223-2232.
|
| [15] |
LI B, REN W, FU D, et al. Benchmarking single-image dehazing and beyond[J]. IEEE Transactions on Image Processing, 2019, 28(1): 492-505.
|
| [16] |
ANCUTI C O, ANCUTI C, TIMOFTE R, et al. O-HAZE: A dehazing benchmark with real hazy and haze-free outdoor images[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . Piscataway: IEEE Press, 2018: 754-762.
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