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Multitask Learning Mechanism for Remote Sensing Image Motion Deblurring
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 As a fundamental preprocessing technique, remote sensing image motion deblurring is important for visual understanding tasks. Most conventional approaches formulate the image motion deblurring task as a kernel estimation. Because the kernel estimation is
Jie Fang +3 more
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Forward Motion Deblurring [PDF]
2013 IEEE International Conference on Computer Vision, 2013 We handle a special type of motion blur considering that cameras move primarily forward or backward. Solving this type of blur is of unique practical importance since nearly all car, traffic and bike-mounted cameras follow out-of-plane translational motion.
Shicheng Zheng, Li Xu 0001, Jiaya Jia
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RAID-Net: Region-Aware Image Deblurring Network Under Guidance of the Image Blur Formulation
IEEE Access, 2022 Image deblurring is a challenging field in computational photography and computer vision. In the deep learning era, deblurring methods boosted with neural networks achieve significant results.
Lianjun Liao, Zihao Zhang, Shihong Xia
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Gradient-wise search strategy for blind image deblurring [PDF]
MATEC Web of Conferences, 2022 Blind image deblurring is a long-standing challenging problem to improve the sharpness of an image as a prerequisite step. Many iterative methods are widely used for the deblurring image, but care must be taken to ensure that the methods have fast ...
Wang Yunhong, Liu Dan
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Human-Aware Motion Deblurring [PDF]
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 This paper proposes a human-aware deblurring model that disentangles the motion blur between foreground (FG) humans and background (BG). The proposed model is based on a triple-branch encoder-decoder architecture. The first two branches are learned for sharpening FG humans and BG details, respectively; while the third one produces global, harmonious ...
Ziyi Shen +6 more
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Motion Deblurring for Single Photograph Based on Particle Swarm Optimization [PDF]
International Journal of Computational Intelligence Systems, 2014 This paper addresses the issue of non-uniform motion deblurring for a single photograph. The main difficulty of spatially variant motion deblurring is that, the deconvolution algorithm can not directly be used to estimate blur kernel, due to the kernel ...
Jing Wei +3 more
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MedDeblur: Medical Image Deblurring with Residual Dense Spatial-Asymmetric Attention
Mathematics, 2022 Medical image acquisition devices are susceptible to producing blurry images due to respiratory and patient movement. Despite having a notable impact on such blind-motion deblurring, medical image deblurring is still underexposed.
S. M. A. Sharif +5 more
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Real-World Deep Local Motion Deblurring [PDF]
, 2023 Most existing deblurring methods focus on removing global blur caused by camera shake, while they cannot well handle local blur caused by object movements.
Feng, Huajun +5 more
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Edge Detection of Motion-Blurred Images Aided by Inertial Sensors
Sensors, 2023 Edge detection serves as the foundation for advanced image processing tasks. The accuracy of edge detection is significantly reduced when applied to motion-blurred images.
Luo Tian +3 more
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Motion deblurring in human vision [PDF]
Proceedings of the Royal Society of London. Series B: Biological Sciences, 1997 Under normal viewing conditions we are little conscious of blur in moving objects, despite the persistence of vision. Moving objects look more blurred in brief than in long exposures, suggesting an active mechanism for suppressing motion blur.
BURR, DAVID CHARLES, M. J. Morgan
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