Results 51 to 60 of about 2,423 (185)

Survey on Image Deblurring Algorithms [PDF]

Jisuanji kexue
Image deblurring is a classic problem in computer vision,aiming to recover sharp visual information from blurry input images or videos.Blur is often caused by factors such as camera misfocus,camera shake,or fast-moving objects.Traditional deblurring ...
CHEN Kang, LIN Jianhan, LIU Yuanjie
doaj   +1 more source

Automatic Classification of Pollen Grain Microscope Images Using a Multi-Scale Classifier with SRGAN Deblurring

Applied Sciences, 2022
Pollen allergies are seasonal epidemic diseases that are accompanied by high incidence rates, especially in Beijing, China. With the development of deep learning, key progress has been made in the task of automatic pollen grain classification, which ...
Xingyu Chen, Fujiao Ju
doaj   +1 more source

Depiction Fidelity and Specificity in Direct MRI of Collagen: Addressing Signal Decay at the Microsecond Timescale

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Gap‐filled zero echo time (ZTE) acquisitions combined with dedicated short‐T2 hardware enable direct collagen imaging on the timescale of macromolecular (MM) signals, with T2s ˜ 10 μs. However, present methods offer limited depiction fidelity, and their specificity towards MM content is poorly understood. This work presents methodology
Jason Daniel van Schoor, Markus Weiger, Emily Louise Baadsvik, Klaas Paul Pruessmann   +3 more
wiley   +1 more source

VDTR: Video Deblurring With Transformer

IEEE Transactions on Circuits and Systems for Video Technology, 2023
Video deblurring is still an unsolved problem due to the challenging spatio-temporal modeling process. While existing convolutional neural network-based methods show a limited capacity for effective spatial and temporal modeling for video deblurring. This paper presents VDTR, an effective Transformer-based model that makes the first attempt to adapt ...
Mingdeng Cao, Yanbo Fan, Yong Zhang 0034, Jue Wang 0001, Yujiu Yang 0001   +4 more
openaire   +2 more sources

Texture-Aware Deblurring for Remote Sensing Images Using $ \ell _0$-Based Deblurring and $ \ell _2$-Based Fusion

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
This article presents an image deblurring method using ℓ0-norm-based deblurring and ℓ2-norm-based texture-aware image fusion for remote sensing images.
Heunseung Lim, Soohwan Yu, Kwanwoo Park, Doochun Seo, Joonki Paik   +4 more
doaj   +1 more source

A Comprehensive Review of Deep Learning-Based Real-World Image Restoration

IEEE Access, 2023
Real-world imagery does not always exhibit good visibility and clean content, but often suffers from various kinds of degradations (e.g., noise, blur, rain drops, fog, color distortion, etc.), which severely affect vision-driven tasks (e.g., image ...
Lujun Zhai, Yonghui Wang, Suxia Cui, Yu Zhou   +3 more
doaj   +1 more source

A user‐friendly platform for deep‐learning‐based image enhancement in scanning X‐ray microscopy

Journal of Synchrotron Radiation, EarlyView.
A graphical user interface is developed for deep‐learning‐based image enhancement in scanning X‐ray microscopy. By incorporating the intensity of the probe and scan parameters, the graphical user interface enables accessible and reproducible super‐resolution and deblurring of scanning X‐ray datasets, supporting improved analysis of X‐ray fluorescence ...
Xiaoyin Zheng, Zirui Gao, Ajith Pattammattel, Hanfei Yan, Mingyuan Ge, Yong S. Chu, Yu-chen Karen Chen-Wiegart, Xiaojing Huang   +7 more
wiley   +1 more source

SAM-DEBLUR: Let Segment Anything Boost Image Deblurring

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Image deblurring is a critical task in the field of image restoration, aiming to eliminate blurring artifacts. However, the challenge of addressing non-uniform blurring leads to an ill-posed problem, which limits the generalization performance of existing deblurring models.
Siwei Li, Mingxuan Liu 0001, Yating Zhang, Shu Chen, Haoxiang Li, Hong Chen 0002, Zifei Dou   +6 more
openaire   +2 more sources

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

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