Single image super-resolution with dilated convolution based multi-scale information learning inception module

Proceedings - International Conference on Image Processing, ICIP

Volumn 2017-September, Issue , 2017, Pages 977-981

  Shi, Wuzhen ^a   Jiang, Feng ^a   Zhao, Debin ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Convolutional neural network; Dilated convolution; Image super resolution; Inception module; Multi scale information

Indexed keywords

COMPUTER VISION; DEEP LEARNING; IMAGE ENHANCEMENT; IMAGE RECONSTRUCTION; NEURAL NETWORKS; OPTICAL RESOLVING POWER; RESTORATION;

'CURRENT; CONVOLUTIONAL NEURAL NETWORK; DILATED CONVOLUTION; IMAGE SUPER RESOLUTIONS; INCEPTION MODULE; LEARN+; MULTISCALE INFORMATION; NATURAL IMAGES; PERFORMANCE; SINGLE IMAGES;

CONVOLUTION;

EID: 85045319019     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2017.8296427     Document Type: Conference Paper

References (22)

1. Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich, "Going deeper with convolutions, " in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 1-9.
2. Armin Kappeler, Seunghwan Yoo, Qiqin Dai, and Aggelos K Katsaggelos, "Video super-resolution with convolutional neural networks, " IEEE Transactions on Computational Imaging, vol. 2, no. 2, pp. 109-122, 2016.
3. Jianchao Yang, John Wright, Thomas S Huang, and Yi Ma, "Image super-resolution via sparse representation, " IEEE transactions on image processing, vol. 19, no. 11, pp. 2861-2873, 2010.
4. Daniel Glasner, Shai Bagon, and Michal Irani, "Superresolution from a single image, " in Computer Vision, 2009 IEEE 12th International Conference on. IEEE, 2009, pp. 349-356.
5. Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang, "Learning a deep convolutional network for image super-resolution, " in European Conference on Computer Vision. Springer, 2014, pp. 184-199.
6. Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang, "Image super-resolution using deep convolutional networks, " IEEE transactions on pattern analysis and machine intelligence, vol. 38, no. 2, pp. 295-307, 2016.
7. Chao Dong, Yubin Deng, Chen Change Loy, and Xiaoou Tang, "Compression artifacts reduction by a deep convolutional network, " in Proceedings of the IEEE International Conference on Computer Vision, 2015, pp. 576-584.
8. Chao Dong, Chen Change Loy, and Xiaoou Tang, "Accelerating the super-resolution convolutional neural network, " in European Conference on Computer Vision. Springer, 2016, pp. 391-407.
9. Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee, "Accurate image super-resolution using very deep convolutional networks, " in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 1646-1654.
10. Matthias Holschneider, Richard Kronland-Martinet, Jean Morlet, and Ph Tchamitchian, "A real-time algorithm for signal analysis with the help of the wavelet transform, " in Wavelets, pp. 286-297. Springer, 1990.
11. Mark J Shensa, "The discrete wavelet transform: wedding the a trous and mallat algorithms, " IEEE Transactions on signal processing, vol. 40, no. 10, pp. 2464-2482, 1992.
12. Fisher Yu and Vladlen Koltun, "Multi-scale context aggregation by dilated convolutions, " arXiv preprint arXiv: 1511. 07122, 2015.
13. Clément Farabet, Camille Couprie, Laurent Najman, and Yann LeCun, "Scene parsing with multiscale feature learning, purity trees, and optimal covers, " arXiv preprint arXiv: 1202. 2160, 2012.
14. Diederik Kingma and Jimmy Ba, "Adam: A method for stochastic optimization, " arXiv preprint arXiv: 1412. 6980, 2014.
15. Marco Bevilacqua, Aline Roumy, Christine Guillemot, and Marie Line Alberi-Morel, "Low-complexity singleimage super-resolution based on nonnegative neighbor embedding, " in Proceedings of the British Machine Vision Conference. 2012, pp. 135. 1-135. 10, BMVA Press.
16. Roman Zeyde, Michael Elad, and Matan Protter, "On single image scale-up using sparse-representations, " in International conference on curves and surfaces. Springer, 2010, pp. 711-730.
17. David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik, "A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, " in Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on. IEEE, 2001, vol. 2, pp. 416-423.
18. Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, "Delving deep into rectifiers: Surpassing humanlevel performance on imagenet classification, " in Proceedings of the IEEE international conference on computer vision, 2015, pp. 1026-1034.
19. Jun Guo and Hongyang Chao, "Building dual-domain representations for compression artifacts reduction, " in European Conference on Computer Vision. Springer, 2016, pp. 628-644.
20. Radu Timofte, Vincent De Smet, and Luc Van Gool, "A+: Adjusted anchored neighborhood regression for fast super-resolution, " in Asian Conference on Computer Vision. Springer, 2014, pp. 111-126.
21. Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, "Delving deep into rectifiers: Surpassing humanlevel performance on imagenet classification, " in Proceedings of the IEEE international conference on computer vision, 2015, pp. 1026-1034.
22. Z Wang, D Liu, J Yang, W Han, and T Huang, "Deeply improved sparse coding for image super-resolution. Arxiv preprint, " arXiv preprint arXiv: 1507. 08905, vol. 2, no. 3, pp. 4, 2015.