Results 51 to 60 of about 9,140,641 (221)

Deblurring Face Images with Exemplars [PDF]

, 2014
The human face is one of the most interesting subjects involved in numerous applications. Significant progress has been made towards the image deblurring problem, however, existing generic deblurring methods are not able to achieve satisfying results on blurry face images.
Jin-shan Pan, Zhe Hu, Zhixun Su, Ming-Hsuan Yang 0001   +3 more
openaire   +1 more source

Separable Kernel for Image Deblurring [PDF]

2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
In this paper, we deal with the image deblurring problem in a completely new perspective by proposing separable kernel to represent the inherent properties of the camera and scene system. Specifically, we decompose a blur kernel into three individual descriptors (trajectory, intensity and point spread function) so that they can be optimized separately.
Lu Fang 0001, Haifeng Liu, Feng Wu 0001, Xiaoyan Sun 0001, Houqiang Li   +4 more
openaire   +1 more source

Deep Residual Combiner: A Learned Fusion of Spatial, Temporal, and Multiscale Correlated Pixel Estimates

Computer Graphics Forum, EarlyView.
Abstract Correlation‐based rendering techniques continue to advance, and efficiently exploiting correlations between pixel estimates has become increasingly important. The deep combiner framework [BHHM20] allows us to fuse independent and correlated pixel estimates but focuses solely on spatial correlations.
W. Zhou, E. Hughes, T. Hachisuka
wiley   +1 more source

Motion Deblurring from a Single Image [PDF]

, 2018
With the information explosion, a tremendous amount photos is captured and shared via social media everyday. Technically, a photo requires a finite exposure to accumulate light from the scene. Thus, objects moving during the exposure generate motion blur
Jin, Meiguang
core  

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

International Endodontic Journal, EarlyView.
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi, Sanyam Jain, Khuram Naveed, Sepanta Hosseinpour, Lise‐Lotte Kirkevang, Ali Nosrat, Ruben Pauwels   +6 more
wiley   +1 more source

An image defocus deblurring method based on gradient difference of boundary neighborhood

Virtual Reality & Intelligent Hardware, 2023
Background: For static scenes with multiple depth layers, the existing defocused image deblurring methods have the problems of edge ringing artifacts or insufficient deblurring degree due to inaccurate estimation of blur amount, In addition, the prior ...
Junjie TAO, Yinghui WANG, Haomiao M.A, Tao YAN, Lingyu AI, Shaojie ZHANG, Wei LI   +6 more
doaj   +1 more source

Semantic-aware Image Deblurring

CoRR, 2019
Image deblurring has achieved exciting progress in recent years. However, traditional methods fail to deblur severely blurred images, where semantic contents appears ambiguously. In this paper, we conduct image deblurring guided by the semantic contents inferred from image captioning.
Fuhai Chen, Rongrong Ji, Chengpeng Dai, Xiaoshuai Sun, Chia-Wen Lin, Jiayi Ji, Baochang Zhang 0001, Feiyue Huang, Liujuan Cao   +8 more
openaire   +3 more sources

Fast Localized Calibration for Spatial‐Spectral Excitation Without Fly‐Back Gradients

Magnetic Resonance in Medicine, Volume 96, Issue 5, Page 2253-2265, November 2026.
ABSTRACT Purpose Standard spatial‐spectral excitation pulses apply a fly‐back gradient between sub‐pulses, limiting, for example, how thin the slices can be (> 4 mm). Without fly‐back gradients, slices can be as thin as 1.7 mm but require a phase calibration for the sub‐pulses with inverted gradients due to system imperfections.
Michael Schär, Sandeep K. Ganji, Robert G. Weiss, Allison G. Hays   +3 more
wiley   +1 more source

Joint Non-Local Statistical and Wavelet Tight Frame Information-Based ℓ₀ Regularization Model for Image Deblurring

IEEE Access
The task of image deblurring is a complex and ill-posed inverse problem, which endeavors to restore a high-fidelity image from its degraded and blurred counterpart.
Yongqun Tan, Lingli Zhang, Yu Chen
doaj   +1 more source

Image deblurring method driven by double layer convolution neural network denoising module

Nantong Daxue xuebao. Ziran kexue ban, 2022
To solve this problem for inflexible of noise levels for deep convolution neural network for image denoising, an image deblurring method driven by a double deep convolution neural network for image denoising is proposed.The learning capability of ...
WU Jingjing; MA Jingning; ZHU Yonggui
doaj   +1 more source