Results 31 to 40 of about 15,742 (208)
Stochastic Blind Motion Deblurring [PDF]
IEEE Transactions on Image Processing, 2015 Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can, therefore, only be obtained with the help of prior information in the form of (often nonconvex) regularization terms for both the intrinsic image and the kernel.
Xiao, Lei +3 more
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
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
Motion Deblurring of Faces [PDF]
International Journal of Computer Vision, 2018 Face analysis is a core part of computer vision, in which remarkable progress has been observed in the past decades. Current methods achieve recognition and tracking with invariance to fundamental modes of variation such as illumination, 3D pose, expressions.
Grigorios G. Chrysos +2 more
openaire +5 more sources
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
core +1 more source
A multi-task approach to face deblurring
EURASIP Journal on Wireless Communications and Networking, 2019 Image deblurring is a foundational problem with numerous application, and the face deblurring subject is one of the most interesting branches. We propose a convolutional neural network (CNN)-based architecture that embraces multi-scale deep features.
Ziyi Shen +4 more
doaj +1 more source
WIG-Net: Wavelet-Based Defocus Deblurring with IFA and GCN
Applied Sciences, 2023 Although the existing deblurring methods for defocused images are capable of approximately recovering clear images, they still exhibit certain limitations, such as ringing artifacts and remaining blur.
Yi Li, Nan Wang, Jinlong Li, Yu Zhang
doaj +1 more source
Learning to Deblur Images with Exemplars
, 2018 Human faces are one interesting object class with numerous applications. While significant progress has been made in the generic deblurring problem, existing methods are less effective for blurry face images.
Hu, Zhe +3 more
core +1 more source
Digital Deblurring of CMB Maps II: Asymmetric Point Spread Function [PDF]
, 2003 In this second paper in a series dedicated to developing efficient numerical techniques for the deblurring Cosmic Microwave Background (CMB) maps, we consider the case of asymmetric point spread functions (PSF).
Baccigalupi +14 more
core +2 more sources
Joint Blind Motion Deblurring and Depth Estimation of Light Field
, 2018 Removing camera motion blur from a single light field is a challenging task since it is highly ill-posed inverse problem. The problem becomes even worse when blur kernel varies spatially due to scene depth variation and high-order camera motion.
A Beck +12 more
core +1 more source