Results 21 to 30 of about 946,624 (201)
An Edge-Enhanced Branch for Multi-Frame Motion Deblurring
IEEE AccessNon-uniform deblurring is one of the most important image restoration tasks for providing appropriate information for subsequent applications that require image recognition.
Sota Moriyama, Koichi Ichige
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Motion Deblurring in Image Color Enhancement by WGAN
International Journal of Optics, 2020 Motion deblurring and image enhancement are active research areas over the years. Although the CNN-based model has an advanced state of the art in motion deblurring and image enhancement, it fails to produce multitask results when challenged with the ...
Jiangfan Feng, Shuang Qi
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Motion Deblurring from a Single Image [PDF]
, 2018 With the information explosion, a tremendous amount photos is captured and shared via social media everyday. Technically, a photo requires a finite exposure to accumulate light from the scene. Thus, objects moving during the exposure generate motion blur in a photo. Motion blur is an image degradation that makes visual content less interpretable and is
Jin, Meiguang
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Motion Blur Removal for Uav-Based Wind Turbine Blade Images Using Synthetic Datasets
Remote Sensing, 2021 Unmanned air vehicle (UAV) based imaging has been an attractive technology to be used for wind turbine blades (WTBs) monitoring. In such applications, image motion blur is a challenging problem which means that motion deblurring is of great significance ...
Yeping Peng +4 more
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Human and Scene Motion Deblurring Using Pseudo-Blur Synthesizer
IEEE Access, 2021 Present-day deep learning-based motion deblurring methods utilize the pair of synthetic blur and sharp data to regress any particular framework. This task is designed for directly translating a blurry image input into its restored version as output.
Jonathan Samuel Lumentut, In Kyu Park
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CoRR, 2021 Camera gimbal systems are important in various air or water borne systems for applications such as navigation, target tracking, security and surveillance. A higher steering rate (rotation angle per second) of gimbal is preferable for real-time applications since a given field-of-view (FOV) can be revisited within a short period of time. However, due to
Nisha Varghese +2 more
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Motion Deblurring with Real Events [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 In this paper, we propose an end-to-end learning framework for event-based motion deblurring in a self-supervised manner, where real-world events are exploited to alleviate the performance degradation caused by data inconsistency. To achieve this end, optical flows are predicted from events, with which the blurry consistency and photometric consistency
Fang Xu +7 more
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Motion deblurring as optimisation [PDF]
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing, 2010 Motion blur is one of the most common causes of image degradation. It is of increasing interest due to the deep penetration of digital cameras into consumer applications. In this paper, we start with a hypothesis that there is sufficient information within a blurred image and approach the deblurring problem as an optimisation process where the ...
V. S. Rao Veeravasarapu +1 more
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Infrared Image Deblurring Based on Generative Adversarial Networks
International Journal of Optics, 2021 Blind deblurring of a single infrared image is a challenging computer vision problem. Because the blur is not only caused by the motion of different objects but also by the relative motion and jitter of cameras, there is a change of scene depth.
Yuqing Zhao +4 more
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A domain translation network with contrastive constraint for unpaired motion image deblurring
IET Image Processing, 2023 Most motion deblurring methods require a large amount of paired training data, which is nearly unreachable in practice. To overcome the limitation, a domain translation network with contrastive constraint for unpaired motion image deblurring is proposed.
Bingxin Zhao, Weihong Li
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