Results 31 to 40 of about 108,873 (282)
LCD motion blur estimation using different measurement methods [PDF]
, 2009 International audienceThe primary goal of this study is to find a measurement method for motion blur which is easy to carry out and gives results that can be reproduced from one lab to another. This method should be able to also take into account methods
Andrén, Borje +3 more
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Learning to Synthesize Motion Blur [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 http://timothybrooks.com/tech/motion-blur/ .
Tim Brooks, Jonathan T. Barron
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IMU-aided adaptive mesh-grid based video motion deblurring [PDF]
PeerJ Computer ScienceMotion blur is a problem that degrades the visual quality of images for human perception and also challenges computer vision tasks. While existing studies mostly focus on deblurring algorithms to remove uniform blur due to their computational efficiency,
Ahmet Arslan +2 more
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Restoration of Motion Blurred Images [PDF]
2006 IEEE International Conference on Multimedia and Expo, 2006 In this paper, we present several algorithms developed for restoration of motion blurred images. We begin with a single-image based deblurring approach in the case of linear constant motion. This approach is a wavelet-based method with a novel lp-norm regularization term.
Juwei Lu +2 more
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Motion-blur-free video shooting system based on frame-by-frame intermittent tracking
ROBOMECH Journal, 2017 In this paper, a concept of frame-by-frame intermittent tracking to achieve motion-blur-free and high-brightness images when video shooting fast moving scenes is proposed.
Michiaki Inoue +4 more
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Object Motion Deblurring in Single Image Under Static Background
IEEE Access, 2020 When shooting a moving object, as the object moves too fast or the camera's exposure time is too long, smears may occur in the image, which would result in motion blur. The blind restoration of object motion blur is a challenging inversive problem.
Tengteng Zhang +4 more
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Accurate and Fast Blur Detection Using a Pyramid M-Shaped Deep Neural Network
IEEE Access, 2019 Blur detection is aimed at estimating the probability of each pixel being blurred or non-blurred in an image affected by motion or defocus blur. This task has gained considerable attention due to its promising application fields in computer vision ...
Xuewei Wang +5 more
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Mathematical Problems of Computer Science, 2021 In this paper, we present deep learning-based blind image deblurring methods for estimating and removing a non-uniform motion blur from a single blurry image. We propose two fully convolutional neural networks (CNN) for solving the problem.
Misak T. Shoyan +2 more
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Suboptimal eye movements for seeing fine details. [PDF]
, 2018 Human eyes are never stable, even during attempts of maintaining gaze on a visual target. Considering transient response characteristics of retinal ganglion cells, a certain amount of motion of the eyes is required to efficiently encode information and ...
Agaoglu, Mehmet N +4 more
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Partial Motion Blur Removal [PDF]
2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), 2018 The work is focused on two types of images partial blur (a single object blur and background blur). Complex approach to the deblurring of such images is proposed. It includes such aspects as automated blur detection, blurred image PSF estimation, blurred patches extraction and processing etc.
Andriy Klyuvak +2 more
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