Results 41 to 50 of about 6,569 (169)
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.
Welk, Martin +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
doaj +1 more source
Depth-aware motion deblurring [PDF]
2012 IEEE International Conference on Computational Photography (ICCP), 2012 Motion deblurring from images that are captured in a scene with depth variation needs to estimate spatially-varying point spread functions (PSFs). We tackle this problemwith a stereopsis configuration, using depth information to help blur removal. We observe that the simple scheme to partition the blurred images into regions and estimate their PSFs ...
null Li Xu, null Jiaya Jia
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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
doaj +1 more source
CNN for license plate motion deblurring [PDF]
2016 IEEE International Conference on Image Processing (ICIP), 2016 In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks in a situation where the blur kernels are partially constrained. We focus on blurred images from a real-life traffic surveillance system, on which we, for the first time, demonstrate that neural networks trained on ...
Svoboda, Pavel +3 more
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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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Self-Supervised Linear Motion Deblurring [PDF]
IEEE Robotics and Automation Letters, 2020 Motion blurry images challenge many computer vision algorithms, e.g, feature detection, motion estimation, or object recognition. Deep convolutional neural networks are state-of-the-art for image deblurring. However, obtaining training data with corresponding sharp and blurry image pairs can be difficult.
Peidong Liu +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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Learning Event-Based Motion Deblurring [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Accepted to CVPR ...
Jiang, Zhe +5 more
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Deblurring by Realistic Blurring
, 2020 Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios ...
Li, Hongdong +6 more
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