Results 31 to 40 of about 1,226,194 (284)
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2014 The aim of any image restoration techniques is recovering the original image from a degraded observation. One of the most common degradation phenomena in images is motion blur.
shamik tiwari
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Camouflaged Adversarial Example Generation Method for the Form of Motion Blur in Traffic Scenes [PDF]
Jisuanji gongchengIn the domain of autonomous driving perception systems, Convolutional Neural Network(CNN) plays a pivotal role as a fundamental technology in vehicle perception and decision making. However, adversarial attacks pose a substantial threat to the safety and
ZHANG Zhaoxin, HUANG Shize, ZHANG Bingjie, SHEN Tuo
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INTEGRATION OF IMAGE-DERIVED AND POS-DERIVED FEATURES FOR IMAGE BLUR DETECTION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 The image quality plays an important role for Unmanned Aerial Vehicle (UAV)’s applications. The small fixed wings UAV is suffering from the image blur due to the crosswind and the turbulence.
T.-A. Teo, K.-Z. Zhan
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A New Full-Reference Image Quality Metric for Motion Blur Profile Characterization
IEEE Access, 2021 Motion blur is common in images captured by handheld devices, arising from hand, device and/or object motion. To restore sharp images from the images degraded by the motion, it is extremely important to assess the quality of the captured image and its ...
Mohammad Abdullah-Al-Mamun +2 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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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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Spatiotemporal Variance-Guided Filtering for Motion Blur
, 2022 Adding motion blur to a scene can help to convey the feeling of speed even at low frame rates. Monte Carlo ray tracing can compute accurate motion blur, but requires a large number of samples per pixel to converge.
Max Oberberger +5 more
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Motion Offset for Blur Modeling [PDF]
, 2023 Motion blur caused by the relative movement between the camera and the subject is often an undesirable degradation of the image quality. In most conventional deblurring methods, a blur kernel is estimated for image deconvolution.
Zhang, Youjian
core
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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