Results 21 to 30 of about 6,499 (150)
Multi-Stage Network for Event-Based Video Deblurring with Residual Hint Attention
Sensors, 2023 Video deblurring aims at removing the motion blur caused by the movement of objects or camera shake. Traditional video deblurring methods have mainly focused on frame-based deblurring, which takes only blurry frames as the input to produce sharp frames ...
Jeongmin Kim, Yong Ju Jung
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A Blur Restoration Algorithm Based on L0 Regularization [PDF]
Jisuanji gongcheng, 2016 Aiming at the motion blur,a new blind deblurring algorithm is proposed,which is based on the L0 regularization restraints and the prior knowledge of natural image gradient distribution to obtain the real motion kernel.In the proposed methods,T-smooth ...
FANG Shuai,FAN Dong,YU Lei,CAO Fengyun
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Sensors, 2021 Complex marine environment has an adverse effect on the object detection algorithm based on the vision sensor for the smart ship sailing at sea. In order to eliminate the motion blur in the images during the navigation of the smart ship and ensure safety,
Hui Feng +3 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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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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Robust Single Image Deblurring Using Gyroscope Sensor
IEEE Access, 2021 Motion blur in an image is caused by the movement of the camera during exposure time; thus, awareness of the camera motion is a key factor in image deblurring algorithms.
Seowon Ji +4 more
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Differentiable Neural Architecture Search Method for Blind Image Deblurring [PDF]
Jisuanji gongcheng, 2021 The design of neural networks for image deblurring requires heavy work of manual parameter tuning. To address the problem, a differentiable neural network search method for image deblurring is proposed.
MIAO Si, ZHU Yongxin
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Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal [PDF]
, 2015 In this paper, we address the problem of estimating and removing non-uniform motion blur from a single blurry image. We propose a deep learning approach to predicting the probabilistic distribution of motion blur at the patch level using a convolutional ...
Cao, Wenfei +3 more
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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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SID: Sensor-Assisted Image Deblurring System for Mobile Devices
IEEE Access, 2019 Handheld mobile photography is often affected by motion blur due to the difficulty of keeping the camera's stable. The existing processing method is usually a high-cost deblurring process of a computer, which seriously affects the user experience, and ...
Qing Wang +4 more
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