Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (9): 2838-2844.DOI: 10.11772/j.issn.1001-9081.2021081433
• Multimedia computing and computer simulation • Previous Articles
Haiyun WEI, Qianying ZHENG(), Jinling YU
Received:
2021-08-12
Revised:
2021-11-20
Accepted:
2021-11-25
Online:
2022-01-07
Published:
2022-09-10
Contact:
Qianying ZHENG
About author:
WEI Haiyun, born in 1996, M. S. candidate. Her research interests include computer vision, image processing, image restoration.Supported by:
通讯作者:
郑茜颖
作者简介:
魏海云(1996—),女,河南信阳人,硕士研究生,主要研究方向:计算机视觉、图像处理、图像复原;基金资助:
CLC Number:
Haiyun WEI, Qianying ZHENG, Jinling YU. Motion blurred image restoration algorithm based on multi-scale network[J]. Journal of Computer Applications, 2022, 42(9): 2838-2844.
魏海云, 郑茜颖, 俞金玲. 基于多尺度网络的运动模糊图像复原算法[J]. 《计算机应用》唯一官方网站, 2022, 42(9): 2838-2844.
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URL: http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2021081433
算法 | PSNR/dB | SSIM |
---|---|---|
本文算法 | 33.69 | 0.953 7 |
无注意力机制的算法 | 30.45 | 0.924 4 |
Tab. 1 Influence of attention mechanism on experimental results
算法 | PSNR/dB | SSIM |
---|---|---|
本文算法 | 33.69 | 0.953 7 |
无注意力机制的算法 | 30.45 | 0.924 4 |
算法 | 参数量/106 | PSNR/dB | SSIM | 复原时间/s |
---|---|---|---|---|
本文算法 | 9.79 | 33.69 | 0.953 7 | 0.013 1 |
无ConvGRU的算法 | 11.25 | 31.73 | 0.939 8 | 0.131 2 |
Tab. 2 Influence of ConvGRU module on experimental results
算法 | 参数量/106 | PSNR/dB | SSIM | 复原时间/s |
---|---|---|---|---|
本文算法 | 9.79 | 33.69 | 0.953 7 | 0.013 1 |
无ConvGRU的算法 | 11.25 | 31.73 | 0.939 8 | 0.131 2 |
数据集 | 算法 | PSNR/dB | SSIM | 复原时间/s |
---|---|---|---|---|
GoPro 数据集 | 传统盲去模糊算法 | 25.04 | 0.801 2 | 32.114 2 |
CNN | 26.75 | 0.871 0 | 5.478 2 | |
SRN | 31.58 | 0.914 0 | 0.402 3 | |
DMPHN | 32.47 | 0.935 1 | 0.234 1 | |
本文算法 | 33.69 | 0.9537 | 0.0131 | |
Blur 数据集 | 传统盲去模糊算法 | 24.17 | 0.781 4 | 38.197 8 |
CNN | 25.22 | 0.852 1 | 10.631 0 | |
SRN | 30.14 | 0.875 6 | 0.812 1 | |
DMPHN | 31.01 | 0.892 4 | 0.350 1 | |
本文算法 | 31.47 | 0.9047 | 0.1190 |
Tab. 3 Comparison results of the proposed algorithm and other algorithms
数据集 | 算法 | PSNR/dB | SSIM | 复原时间/s |
---|---|---|---|---|
GoPro 数据集 | 传统盲去模糊算法 | 25.04 | 0.801 2 | 32.114 2 |
CNN | 26.75 | 0.871 0 | 5.478 2 | |
SRN | 31.58 | 0.914 0 | 0.402 3 | |
DMPHN | 32.47 | 0.935 1 | 0.234 1 | |
本文算法 | 33.69 | 0.9537 | 0.0131 | |
Blur 数据集 | 传统盲去模糊算法 | 24.17 | 0.781 4 | 38.197 8 |
CNN | 25.22 | 0.852 1 | 10.631 0 | |
SRN | 30.14 | 0.875 6 | 0.812 1 | |
DMPHN | 31.01 | 0.892 4 | 0.350 1 | |
本文算法 | 31.47 | 0.9047 | 0.1190 |
1 | SHAN Q, JIA J Y, AGARWALA A. High-quality motion deblurring from a single image[J]. ACM Transactions on Graphics, 2008, 27(3): No.73. 10.1145/1360612.1360672 |
2 | WHYTE O, SIVIC J, ZISSERMAN A, et al. Non-uniform deblurring for shaken images[C]// Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2010: 491-498. 10.1109/cvpr.2010.5540175 |
3 | CHO T S, PARIS S, HORN B K P, et al. Blur kernel estimation using the Radon transform[C]// Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2011: 241-248. 10.1109/cvpr.2011.5995479 |
4 | HIRSCH M, SCHULER C J, HARMELING S, et al. Fast removal of non-uniform camera shake[C]// Proceedings of the 2011 International Conference on Computer Vision. Piscataway: IEEE, 2011: 463-470. 10.1109/iccv.2011.6126276 |
5 | ANGER J, FACCIOLO G, DELBRACIO M. Estimating an image’s blur kernel using natural image statistics, and deblurring it: an analysis of the Goldstein-Fattal method[J]. Image Processing On Line, 2018, 8: 282-304. 10.5201/ipol.2018.211 |
6 | PAN J S, REN W Q, HU Z, et al. Learning to deblur images with exemplars[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, 41(6): 1412-1425. 10.1109/tpami.2018.2832125 |
7 | SHENG B, LI P, FANG X X, et al. Depth-aware motion deblurring using loopy belief propagation[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2020, 30(4): 955-969. 10.1109/tcsvt.2019.2901629 |
8 | 耿源谦,吴传生,刘文. 混合非凸非光滑正则化约束的模糊图像盲复原[J]. 计算机应用, 2020, 40(4): 1171-1176. 10.11772/j.issn.1001-9081.2019091647 |
GENG Y Q, WU C S, LIU W. Mixed non-convex and non-smooth regularization constraint based blind image restoration[J]. Journal of Computer Applications, 2020, 40(4):1171-1176. 10.11772/j.issn.1001-9081.2019091647 | |
9 | SUN J, CAO W F, XU Z B, et al. Learning a convolutional neural network for non-uniform motion blur removal[C]// Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2015: 769-777. 10.1109/cvpr.2015.7298677 |
10 | SCHULER C J, HIRSCH M, HARMELING S, et al. Learning to deblur[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016, 38(7): 1439-1451. 10.1109/tpami.2015.2481418 |
11 | NAH S, KIM T H, LEE K M. Deep multi-scale convolutional neural network for dynamic scene deblurring[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2017: 257-265. 10.1109/cvpr.2017.35 |
12 | KUPYN O, MARTYNIUK T, WU J R, et al. DeblurGAN-v2: deblurring (orders-of-magnitude) faster and better[C]// Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision. Piscataway: IEEE, 2019: 8877-8886. 10.1109/iccv.2019.00897 |
13 | BAI Y C, JIA H Z, JIANG M, et al. Single-image blind deblurring using multi-scale latent structure prior[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2020, 30(7): 2033-2045. |
14 | PARK D, KANG D U, KIM J, et al. Multi-temporal recurrent neural networks for progressive non-uniform single image deblurring with incremental temporal training[C]// Proceedings of the 2020 European Conference on Computer Vision, LNCS 12351. Cham: Springer, 2020: 327-343. |
15 | CHEN L Y, LU X, ZHANG J, et al. HINet: half instance normalization network for image restoration[C]// Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2021: 182-192. 10.1109/cvprw53098.2021.00027 |
16 | 林晨,尹增山. 基于注意力机制的图像盲去模糊算法[J]. 计算机应用, 2020, 40(S2): 151-157. 10.11772/j.issn.1001-9081.2020030365 |
LIN C, YIN Z S. Attention-based algorithm for image blind deblurring[J]. Journal of Computer Applications, 2020, 40(S2): 151-157. 10.11772/j.issn.1001-9081.2020030365 | |
17 | WOO S, PARK J, LEE J Y, et al. CBAM: convolutional block attention module[C]// Proceedings of the 2018 European Conference on Computer Vision, LNCS 11211. Cham: Springer, 2018: 3-19. |
18 | JOHNSON J, ALAHI A, LI F F. Perceptual losses for real-time style transfer and super-resolution[C]// Proceedings of the 2016 European Conference on Computer Vision, LNCS 9906. Cham: Springer, 2016: 694-711. |
19 | HE K M, ZHANG K Y, REN S Q, et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(9): 1904-1916. 10.1109/tpami.2015.2389824 |
20 | WANG F, JIANG M Q, QIAN C, et al. Residual attention network for image classification[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2017: 6450-6458. 10.1109/cvpr.2017.683 |
21 | SU S C, DELBRACIO M, WANG J. Deep video deblurring for hand-held cameras[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2017: 237-246. 10.1109/cvpr.2017.33 |
22 | GUPTA A, JOSHI N, ZITNICK C L, et al. Single image deblurring using motion density functions[C]// Proceedings of the 2010 European Conference on Computer Vision, LNCS 6311. Berlin: Springer, 2010: 171-184. |
23 | TAO X, GAO H Y, SHEN X Y, et al. Scale-recurrent network for deep image deblurring[C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2018: 8174-8182. 10.1109/cvpr.2018.00853 |
24 | ZHANG H G, DAI Y C, LI H D, et al. Deep stacked hierarchical multi-patch network for image deblurring[C]// Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2019: 5971-5979. 10.1109/cvpr.2019.00613 |
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