Results 51 to 60 of about 14,030 (199)

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, C. Baccigalupi, de Bernardis, Haslam, J. G. Nagy, Kamm, L. Tenorio, Maino, P. Andreani, Pryke, R. Vio, Schlegel, Tegmark, Vio, W. Wamsteker   +14 more
core   +2 more sources

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

Motion Deblurring in the Wild

, 2017
The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the ...
A Chakrabarti, A Gupta, CJ Schuler, L Xiao, L Xu, P Wieschollek, R Fergus, R Köhler, S Cho, SD Babacan, T Michaeli   +10 more
core   +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   +2 more sources

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

Zero-shot realistic image deblurring with consistency model

Complex & Intelligent Systems
At present, diffusion-based image deblurring methods rely on paired blurry-clear datasets for training, and the types of blur causes in image synthesis cannot yet be determined with sufficient precision to model real-world scene blur datasets ...
Zhaohan Wang, Chengjun Chen, Chenggang Dai   +2 more
doaj   +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

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

BM3D Frames and Variational Image Deblurring

, 2011
A family of the Block Matching 3-D (BM3D) algorithms for various imaging problems has been recently proposed within the framework of nonlocal patch-wise image modeling [1], [2].
Danielyan, Aram, Egiazarian, Karen, Katkovnik, Vladimir   +2 more
core   +1 more source

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