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2023 | OriginalPaper | Buchkapitel

Deraining of Image Using UNet-Based Conditional Generative Adversarial Network

verfasst von : Samprit Bose, Deep R. Chavan, Maheshkumar H. Kolekar

Erschienen in: Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security

Verlag: Springer Nature Singapore

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Abstract

Adverse weather conditions like rain, fog and storm cause degradation in the quality of an image. Computer vision operations such as detection, classification and various monitoring of objects activities are adversely affected due to image degradation. Hence, image enhancement is an important pre-processing step. We propose a method for the elimination of rain streaks from rain-affected images by making use of conditional generative adversarial networks. We have used structural similarity index measure and peak signal-to-noise ratio as evaluation metrics evaluate the model. We have tested our model on one synthetic and four real-world datasets and compared the performance with other state-of-the-art methods. We have obtained a generated image that has a close resemblance with the ground truth images.

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Vorheriges Kapitel Opinion Mining-Assisted Intelligent Program Selection Employing Fuzzy SWARA Mechanism

Nächstes Kapitel Video Indexing and Retrieval Techniques: A Review

Bhatnagar S, Ghosal D, Kolekar MH (2017) Classification of fashion article images using convolutional neural networks. In: 2017 fourth international conference on image information processing (ICIIP). IEEE, pp 1–6

Bose S, Ramesh CD, Kolekar MH (2022) Vehicle classification and counting for traffic video monitoring using yolo-v3. In: 2022 international conference on connected systems and intelligence (CSI). IEEE, pp 1–8

Aslam N, Rai PK, Kolekar MH (2022) A3n: attention-based adversarial au-toencoder network for detecting anomalies in video sequence. J Vis Commun Image Represent 87:103598CrossRef

Kolekar MH, Sengupta S (2015) Bayesian network-based customized highlight gen-eration for broadcast soccer videos. IEEE Trans Broadcast 61(2):195–209CrossRef

Kolekar MH (2011) Bayesian belief network based broadcast sports video indexing. Multimed Tools Appl 54(1):27–54CrossRef

Hu M, Yang J, Ling N, Liu Y, Fan J (2022) Lightweight single image deraining algorithm incorporating visual saliency. IET Image Process

Wang Q, Sun G, Dong J, Zhang Y (2022) Pfdn: pyramid feature decoupling net-work for single image deraining. IEEE Trans Image Process 31:7091–7101CrossRef

Cai L, Fu Y, Huo W, Xiang Y, Zhu T, Zhang Y, Zeng H, Zeng D (2022) Multi-scale attentive image de-raining networks via neural architecture search. IEEE Trans Circuits Syst Video Technol

Li P, Jin J, Jin G, Fan L, Gao X, Song T, Chen X (2022) Deep scale-space mining network for single image deraining. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 4276–4285

10.

Wei Y, Zhang Z, Wang Y, Zhang H, Zhao M, Xu M, Wang M (2021) Semi-deraingan: a new semi-supervised single image deraining. In: 2021 IEEE international conference on multimedia and expo (ICME). IEEE, pp 1–6

11.

Jiang K, Wang Z, Yi P, Chen C, Han Z, Lu T, Huang B, Jiang J (2020) Decom-position makes better rain removal: an improved attention-guided deraining net-work. IEEE Trans Circuits Syst Video Technol 31(10):3981–3995CrossRef

12.

Yang W, Tan RT, Feng J, Liu J, Guo Z, Yan S (2017) Deep joint rain detection and removal from a single image. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1357–1366

13.

Yasarla R, Patel VM (2019) Uncertainty guided multi-scale residual learning-using a cycle spinning cnn for single image de-raining. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 8405–8414

14.

Wang T, Yang X, Xu K, Chen S, Zhang Q, Lau RW (2019) Spatial attentive single-image deraining with a high quality real rain dataset. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 12 270–12 279

15.

Dai B, Fidler S, Urtasun R, Lin D (2017) Towards diverse and natural image descriptions via a conditional gan. In: Proceedings of the IEEE international con-ference on computer vision, pp 2970–2979

16.

Isola P, Zhu JY, Zhou T, Efros AA (2017) Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1125–1134

17.

Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation. In: International conference on medical image computing and computer-assisted intervention. Springer, 234–241

18.

Larsen ABL, Sønderby SK, Larochelle H, Winther O (2016) Autoencoding beyond pixels using a learned similarity metric. In: International conference on machine learning. PMLR, pp 1558–1566

19.

Luo Y, Xu Y, Ji H (2015) Removing rain from a single image via discriminative sparse coding. In: Proceedings of the IEEE international conference on computer vision, pp 3397–3405

20.

Eigen D, Krishnan D, Fergus R (2013) Restoring an image taken through a window covered with dirt or rain. In: Proceedings of the IEEE international conference on computer vision, pp. 633–640

21.

Fu X, Huang J, Ding X, Liao Y, Paisley J (2017) Clearing the skies: a deep network architecture for single-image rain removal. IEEE Trans Image Process 26(6):2944–2956MathSciNetCrossRefMATH

22.

Fu X, Liang B, Huang Y, Ding X, Paisley J (2019) Lightweight pyramid networks for image deraining. IEEE Trans Neural Netw Learn Syst 31(6):1794–1807CrossRef

23.

Ren D, Zuo W, Hu Q, Zhu P, Meng D (2019) Progressive image deraining net-works: a better and simpler baseline. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 3937–3946

24.

Wang H, Xie Q, Zhao Q, Liang Y, Meng D (2021) Rcdnet: an interpretable rain convolutional dictionary network for single image deraining. arXiv preprint arXiv:2107.06808

Titel: Deraining of Image Using UNet-Based Conditional Generative Adversarial Network
verfasst von: Samprit Bose
Deep R. Chavan
Maheshkumar H. Kolekar
Verlag: Springer Nature Singapore
Buch: Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security
Print ISBN: 978-981-9914-78-4

Electronic ISBN: 978-981-9914-79-1

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-981-99-1479-1_46

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