Turbulence

1 - Turbulence (3 papers)

O. Oreifej, X. Li, M. Shah, "Simultaneous Video Stabilization and Moving Object Detection in Turbulence", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012.

F. Du, Y. Jin, P. Liu, X. Tang, “An Adaptive Method for Moving Object Detection in Atmospheric Turbulence Environment”, Acta Automatica Sinica, pages 1590-1605, Volume 44, No. 9, 2018.

C. Zhang, F. Zhou, B. Xue, W. Xue, "Stabilization of atmospheric turbulence-distorted video containing moving objects using the monogenic signal", Signal Processing: Image Communication, Volume 63, pages 19–29, 2018.

2- Adverse weather (1 paper)

H. Jung, J. Ju, W. Hwang, J. Kim, "Refining background subtraction using consistent motion detection in adverse weather", SPIE Journal of Electronic Imaging, Volume 28 No. 2, page 020501, 2019.

3 - Rain Streak Removal (20 papers)

3.1 Spatiotemporal Appearance (3 papers)

M. Islam, M. Paul, "Rain Streak Removal From Video Sequence using Spatiotemporal Appearance", Digital Image Computing: Techniques and Applications DICTA 2019, pages 1-7, Perth, Australia, 2019.

M. Islam, M. Paul, M. Antolovich, "Rain Streak Removal with Well-Recovered Moving Objects from Video Sequences Using Photometric Correlation", Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019, pages 3-13, 2019.

M. Islam, M. Paul, "Rain Streak Removal in a Video to Improve Visibility by TAWL Algorithm", Preprint, 2020.

3.2 Matrix/Tensor Decompositions (4 papers)

J. Kim, J. Sim, C. Kim, "Video deraining and desnowing using temporal correlation and low-rank matrix completion", IEEE Transactions on Image Processing, Volume 24, No. 9, pages 2658-2670, 2015.

W. Ren, J. Tian, Z. Han, A. Chan, Y. Tang, "Video desnowing and deraining based on matrix decomposition", IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, pages 4210–4219, 2017.

T. Jiang, T. Huang, X. Zhao, L. Deng, Y. Wang, "A novel tensor-based video rain streaks removal approach via utilizing discriminatively intrinsic priors", IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, pages 2818-2827, 2017.

P. Baiju, S. George, "An Automated Unified Framework for Video Deraining and Simultaneous Moving Object Detection in Surveillance Environments", IEEE Access, 2020.

3.3 Mixture of Gaussians (2 papers)

W. Wei, L. Yi, Q. Xie, Q. Zhao, D. Meng, Z. Xu, "Should we encode rain streaks in video as deterministic or stochastic?", IEEE International Conference on Computer Vision, pages 2616-2525, 2017.

L. Yi, Q. Zhao, W. Wei, Z. Xu, "Robust online rain removal for surveillance videos with dynamic rains", Knowledge-Based Systems, June 2021.

3.4. Sparse Coding (2 papers)

M. Li, Q. Xie, Q. Zhao, W. Wei, S. Gu, J. Tao, D. Meng, "Video rain streak removal by multiscale convolutional sparse coding", IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, pages 6644-6653, 2018.

M. Li, X. Cao, Q. Zhao, L. Zhang, D. Meng, "Online Rain/Snow Removal From Surveillance Videos", IEEE Transactions on Image Processing, Volume 30, pages 2029-2044, 2021.

3.5 Dictonary Learning (1 paper)

Y. Wang, S. Liu, C. Chen, B. Zeng, "A Hierarchical Approach for Rain or Snow Removing in a Single Color Image", IEEE Transactions on Image Processing, Volume 26, pages 3936-3950, 2017.

3.6. Deep Learning (7 papers)

X. Fu, J. Huang, X. Ding, Y. Liao, J. Paisley, "Clearing the skies: A deep network architecture for single-image rain removal", IEEE Transactions on Image Processing, Volume 26, No. 6, pages 2944–2956, 2017.

W. Yang, R.Tan, J. Feng, J. Liu, Z. Guo, S. Ya, "Deep joint rain detection and removal from a single image", IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, pages 1357-1366, 2017.

H. Zhang, V. Patel, “Density-aware single image de-raining using a multi-stream dense network", IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018, 2018.

X. Li, J. Wu, Z. Lin, H. Liu, H. Zha, “Recurrent squeeze-and excitation context aggregation net for single image deraining", European Conference on Computer Vision, ECCV 2018, 2018.

Y. Zheng, X. Yu, M. Liu, S. Zhang, “Residual multiscale based single image deraining.” in British Machine Vision Conference, BMVC 2019, 2019.

W. Yang, R.Tan, J. Feng, Z. Guo, S. Yan, J. Liu, "Joint rain detection and removal from a single image with contextualized deep networks", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 42, No. 6, pages 1377-1393, 2020.

K. Zhang, D. Li, W. Luo, W. Lin, F. Zhao, W. Ren, W. Liu, H. Li, “Enhanced spatio-temporal interaction learning for video deraining: A faster and better framework", Preprint, 2021.

X. Liu, R. Liu, L. Ma, X. Fan, Z. Luo, "Spatial-Temporal Integration Network with Self-Guidance for Robust Video Deraining", IEEE International Conference on Multimedia and Expo, ICME 2021, pages 1-6, 2021.

B. Lu, S. Gai, B. Xiong, J. Wu, “Single image deraining with dual U-Net generative adversarial network”, Multidimensional Systems and Signal Processing, November 2021.

4. Snow Removal (5 papers)

4.1 Image Decomposition (1 paper)

D. Rajderkar, P. Mohod, “Removing snow from an image via image decomposition", IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnolog, ICECCN 2013, pages 576–579, 2013.

4.2 Mixture of Gaussians (1 paper)

B. Yang, Z. Jia, J. Yang, N. Kasabov, "Video Snow Removal Based on Self-adaptation Snow Detection and Patch-based Gaussian Mixture Model", IEEE Access 2020, 2020.

4.3 Deep Learning (3 papers)

Y. Liu, D. Jaw, S. Huang, J. Hwang, “Desnownet: Context-aware deep network for snow removal", IEEE Transactions on Image Processing, Volume 27, No. 6, pages 3064–3073, 2018.

P. Li, M. Yun, J. Tian, Y. Tang, G. Wang, C. Wu, “Stacked dense networks for single-image snow removal,” Neurocomputing, Volume 367, pages 152–163, 2019.

K. Zhang, R. Li, Y. Yu, W. Luo, C. Li, H. Li, “Deep Dense Multi-scale Network for Snow Removal Using Semantic and depth Priors”, IEEE Transactions on Image Processing, 2021.

5- Haze Removal (11 papers)

5.1 Prior Information (6 papers)

Y. Schechner, S. Narasimhan, S. Nayar, “Instant dehazing of images using polarization”, IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001.

]. Shwartz, E. Namer, Y. Schechner, “Blind haze separation”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006, 2006.

S. Nayar, S. Narasimhan, “Vision in bad weather”, IEEE International Conference on Computer Vision, ICCV 1999, pages 820–827, 1999.

S. Narasimhan, S. Nayar, “Chromatic framework for vision in bad weather”, IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000, pages 598-205, 2000.

S. Narasimhan, S. Nayar, “Contrast restoration of weather degraded images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 25, No. 6, pages 713–724, 2003.

S. Narasimhan, S. Nayar, “Vision and the atmosphere”, International Journal of Computer Vision, Volume 48, No. 3, pages 233–254, 2002.

5.2 Deep Learning (5 papers)

B. Cai, X. Xu, K. Jia, C. Qing, D. Tao, “Dehazenet: An end-toend system for single image haze removal”, IEEE Transactions on Image Processing, Volume 25, No. 11, pages 5187–5198, 2016.

W. Ren, S. Liu, H. Zhang, J. Pan, X. Cao, M. Yang, “Single image dehazing via multi-scale convolutional neural networks”, European Conference on Computer Vision, ECCV 2016, 2016.

H. Zhang , V. M. Patel, “Densely connected pyramid dehazing network", IEEE Conference on Computer Vision and Pattern Recognition, pages 3194–3203, 2018.

B. Li, X. Peng, Z. Wang, J. Xu, and D. Feng, “AOD-Net: All-inone dehazing network", IEEE International Conference on Computer Vision, ICCV 2017, 2017

Z. Cheng, S. You, V. Ila, and H. Li, “Semantic single-image dehazing", Preprint. 2018.