Results 51 to 60 of about 6,569 (169)
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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A New Method of Blurring and Deblurring Digital Images Using the Markov Basis
Journal of Kufa for Mathematics and Computer, 2016 In this paper, we introduce a new method of blurring and deblurring digital images using new filters generating from Average filter using HB Markov basis. We call these filters HB-filters. We used these filters to cause a motion blur and then deblurring
Hind Rustum Mohammed +2 more
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Simultaneous Stereo Video Deblurring and Scene Flow Estimation
, 2017 Videos for outdoor scene often show unpleasant blur effects due to the large relative motion between the camera and the dynamic objects and large depth variations. Existing works typically focus monocular video deblurring.
Dai, Yuchao +3 more
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DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks
, 2018 We present DeblurGAN, an end-to-end learned method for motion deblurring. The learning is based on a conditional GAN and the content loss . DeblurGAN achieves state-of-the art performance both in the structural similarity measure and visual appearance ...
Budzan, Volodymyr +4 more
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Joint Blind Motion Deblurring and Depth Estimation of Light Field
, 2018 Removing camera motion blur from a single light field is a challenging task since it is highly ill-posed inverse problem. The problem becomes even worse when blur kernel varies spatially due to scene depth variation and high-order camera motion.
A Beck +12 more
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IEEE Access, 2019 It is of great importance to capture long-range dependency in image deblurring based on deep learning. Existing methods often capture long-range dependency by a large receptive field, which contributes by deep stacks of local convolutional operations ...
Bingxin Zhao, Weihong Li, Weiguo Gong
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Thermal Image Reconstruction Using Deep Learning
IEEE Access, 2020 A high-resolution thermal camera is very expensive and is thus difficult to be used. Furthermore, thermal images become blurred in various cases of object motion, camera shaking, and camera defocusing. To solve these problems, a previous super-resolution
Ganbayar Batchuluun +4 more
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Holistic 3D Body Reconstruction From a Blurred Single Image
IEEE Access, 2022 Holistic human pose and shape reconstruction receive huge interest since it restores detailed human pose and shape including facial expression and finger-level hand shape.
Joshua Santoso, Williem, In Kyu Park
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Motion deblurring using hybrid imaging [PDF]
2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003 Motion blur due to camera motion can significantly degrade the quality of an image. Since the path of the camera motion can be arbitrary, deblurring of motion blurred images is a hard problem. Previous methods to deal with this problem have included blind restoration of motion blurred images, optical correction using stabilized lenses, and special CMOS
M. Ben-Ezra, S.K. Nayar
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Blur-Robust Object Detection Using Feature-Level Deblurring via Self-Guided Knowledge Distillation
IEEE Access, 2022 Images captured from real-world environments often include blur artifacts resulting from camera movement, dynamic object motion, or out-of-focus.
Sung-Jin Cho +3 more
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