Results 31 to 40 of about 2,423 (185)
Meta Transferring for Deblurring
CoRR, 2022 Accepted at BMVC ...
Po-Sheng Liu +5 more
openaire +4 more sources
Forward Motion Deblurring [PDF]
2013 IEEE International Conference on Computer Vision, 2013 We handle a special type of motion blur considering that cameras move primarily forward or backward. Solving this type of blur is of unique practical importance since nearly all car, traffic and bike-mounted cameras follow out-of-plane translational motion.
Shicheng Zheng, Li Xu 0001, Jiaya Jia
openaire +2 more sources
Graph Laplacian for image deblurring [PDF]
ETNA - Electronic Transactions on Numerical Analysis, 2021 Image deblurring is relevant in many fields of science and engineering. To solve this problem, many different approaches have been proposed and among the various methods, variational ones are extremely popular. These approaches are characterized by substituting the original problem with a minimization one where the functional is composed of two terms ...
Bianchi D. +3 more
openaire +4 more sources
Wasserstein Generative Adversarial Network Based De-Blurring Using Perceptual Similarity
Applied Sciences, 2019 The de-blurring of blurred images is one of the most important image processing methods and it can be used for the preprocessing step in many multimedia and computer vision applications. Recently, de-blurring methods have been performed by neural network
Minsoo Hong, Yoonsik Choe
doaj +1 more source
Nonlinear Deblurring for Low-Light Saturated Image
Sensors, 2023 Single image deblurring has achieved significant progress for natural daytime images. Saturation is a common phenomenon in blurry images, due to the low light conditions and long exposure times.
Shuning Cao +4 more
doaj +1 more source
Deblurring by Realistic Blurring [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 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 with sufficient accuracy.
Kaihao Zhang +6 more
openaire +3 more sources
Iterative Blind Deconvolution Algorithm for Deblurring a Single PSP/TSP Image of Rotating Surfaces
Sensors, 2018 Imaging of pressure-sensitive paint (PSP) for pressure measurement on moving surfaces is problematic due to the movement of the object within the finite exposure time of the imager, resulting in the blurring of the blade edges.
Anshuman Pandey, James W. Gregory
doaj +1 more source
Dataset and Network Structure: Towards Frames Selection for Fast Video Deblurring
IEEE Access, 2021 Beyond the underlaying unrealistic presumptions in the existing video deblurring datasets and algorithms which presume that a naturally blurred video is fully blurred. In this work, we define a more realistic video frames averaging-based data degradation
Abdelwahed Nahli +4 more
doaj +1 more source
Symmetrization techniques in image deblurring
ETNA - Electronic Transactions on Numerical Analysis, 2023 This paper presents a couple of preconditioning techniques that can be used to enhance the performance of iterative regularization methods applied to image deblurring problems with a variety of point spread functions (PSFs) and boundary conditions. More precisely, we first consider the anti-identity preconditioner, which symmetrizes the coefficient ...
Donatelli M., Ferrari P., Gazzola S.
openaire +3 more sources
Resolution-Preserving Generative Adversarial Networks for Image Enhancement
IEEE Access, 2019 Generative adversarial networks (GANs) are used for image enhancement such as single image super-resolution (SISR) and deblurring. The conventional GANs-based image enhancement suffers from two drawbacks that cause a quality degradation due to a loss of ...
Donghyeon Lee +4 more
doaj +1 more source