Results 51 to 60 of about 946,624 (201)
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
doaj +1 more source
Fast and Robust linear motion deblurring [PDF]
Signal, Image and Video Processing, 2013 We investigate efficient algorithmic realisations for robust deconvolution of grey-value images with known space-invariant point-spread function, with emphasis on 1D motion blur scenarios. The goal is to make deconvolution suitable as preprocessing step in automated image processing environments with tight time constraints.
Martin Welk +4 more
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A Deep Motion Deblurring Network Using Channel Adaptive Residual Module
IEEE Access, 2021 In this paper, we solve the problem of dynamic scenes deblurring with motion blur. Restoration of images in the presence of motion blur necessitates a network design that the receptive field can completely cover all areas that need to be deblurred, while
Ying Chen +3 more
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Event-Based Fusion for Motion Deblurring with Cross-modal Attention [PDF]
, 2022 Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times. As a kind of bio-inspired camera, the event camera records the intensity changes in an asynchronous way with high temporal resolution, providing valid image ...
Sakaridis, Christos +10 more
core +1 more source
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
Moshe Ben-Ezra, Shree K. Nayar
openaire +2 more sources
Structure-Aware Motion Deblurring Using Multi-Adversarial Optimized CycleGAN
, 2021 Recently, Convolutional Neural Networks (CNNs) have achieved great improvements in blind image motion deblurring. However, most existing image deblurring methods require a large amount of paired training data and fail to maintain satisfactory structural ...
Wen, Yang +6 more
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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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A Video Deblurring Algorithm Based on Motion Vector and An Encorder-Decoder Network
, 2019 Camera shakes cause video motion blur. Video deblurring has been studied for years, and however, there are still unresolved problems, such as video frame alignment, frame selection, and frame ambiguity evaluation.
Li, Li +5 more
core +1 more source
Adaptive Window Pruning for Efficient Local Motion Deblurring [PDF]
, 2023 Local motion blur commonly occurs in real-world photography due to the mixing between moving objects and stationary backgrounds during exposure. Existing image deblurring methods predominantly focus on global deblurring, inadvertently affecting the ...
Zhao, Jixin +5 more
core
Computer Graphics Forum, EarlyView.Abstract Correlationâbased rendering techniques continue to advance, and efficiently exploiting correlations between pixel estimates has become increasingly important. The deep combiner framework [BHHM20] allows us to fuse independent and correlated pixel estimates but focuses solely on spatial correlations.
W. Zhou, E. Hughes, T. Hachisuka
wiley +1 more source