Results 61 to 70 of about 293,019 (211)

Blind Image Deblurring based on Kernel Mixture

CoRR, 2021
Blind Image deblurring tries to estimate blurriness and a latent image out of a blurred image. This estimation, as being an ill-posed problem, requires imposing restrictions on the latent image or a blur kernel that represents blurriness. Different from recent studies that impose some priors on the latent image, this paper regulates the structure of ...
Sajjad Amrollahi Biyouki, Hoon Hwangbo
openaire   +2 more sources

Multi‐Scale Transformer for Image Restoration

CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 41-54, February 2026.
ABSTRACT Although Transformer‐based image restoration methods have demonstrated impressive performance, existing Transformers still insufficiently exploit multiscale information. Previous non‐Transformer‐based studies have shown that incorporating multiscale features is crucial for improving restoration results.
Wuzhen Shi, Youwei Pan, Chun Zhao, Yuqing Liu, Shaobo Zhang, Heng Zhang, Yang Wen   +6 more
wiley   +1 more source

Quasi-Robust Blind Deblurring with Multiple Color Images

, 2011
In this paper, we firstly introduce the limitation and deficiency of L1-norm and L2-norm in deblurring and denoising and the merit of quasi-robust function. Then, we propose a new blind deblurring model using multiple color images.
Rui Hua Liu, Li Yun Su, Fang Li
core   +1 more source

A Motion Deblur Method Based on Multi-Scale High Frequency Residual Image Learning

IEEE Access, 2020
Non-uniform blind deblurring of dynamic scenes has always been a challenging problem in image processing because of the diverse of blurring sources. Traditional methods based on energy minimization cannot make accurate kernel estimation. It leads to that
Keng-Hao Liu, Chia-Hung Yeh, Juh-Wei Chung, Chuan-Yu Chang   +3 more
doaj   +1 more source

Noise-Adaptive Non-Blind Image Deblurring

Sensors, 2022
This work addresses the problem of non-blind image deblurring for arbitrary input noise. The problem arises in the context of sensors with strong chromatic aberrations, as well as in standard cameras, in low-light and high-speed scenarios.
Michael Slutsky
doaj   +1 more source

ESFFA: Early‐Stage Feature Frequency Attack in Cross‐Domain Few‐Shot Learning

IET Computer Vision, Volume 20, Issue 1, January/December 2026.
This paper addresses the challenge of cross‐domain few‐shot learning (CD‐FSL), where models often rely on frequency shortcuts rather than semantic features. We propose ESFFA (Early‐Stage Feature Frequency Attack), a novel method that perturbs low‐frequency statistics and masks high‐frequency components in shallow feature maps to reduce shortcut ...
Xu Wang, Ziyang Cao, Jia Zhao, Huiling Wang, Yingzhou Chen   +4 more
wiley   +1 more source

Collaborative Blind Image Deblurring

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Blurry images usually exhibit similar blur at various locations across the image domain, a property barely captured in nowadays blind deblurring neural networks. We show that when extracting patches of similar underlying blur is possible, jointly processing the stack of patches yields superior accuracy than handling them separately.
Eboli, Thomas, Morel, Jean-Michel, Facciolo, Gabriele   +2 more
openaire   +4 more sources

Fixing a blurred photograph: blind image deblurring

, 2023
This project presents a deep learning-based approach to blind image deblurring using a convolutional neural network. The trained model can produce a deblurred output using only the blurred image as input and exhibits improved image quality, as ...
Teo, Hong Wei
core  

Hybrid Deep Learning Frameworks for License Plate Recognition in Complex Environments: A Comprehensive Survey and Research Outlook

IET Computer Vision, Volume 20, Issue 1, January/December 2026.
This survey systematically reviews state‐of‐the‐art license plate recognition methods, with a focus on hybrid CNN‐transformer frameworks and the joint optimisation of detection and recognition for real‐world deployment. It further analyses existing datasets, highlights persistent challenges, such as domain generalisation, and outlines pathways towards ...
SanXing Deng, Ewe Lay Sheng, Tiong Sieh Kiong, MengMeng Yang   +3 more
wiley   +1 more source

Single Image Defocus Deblurring Based on Structural Information Enhancement

IEEE Access
Defocus deblurring is an important task in computer vision that aims to bring images back to clarity. Over recent years, both blind defocuse deblurring and non-blind defocuse deblurring methods have made great progress in the single image defocus ...
Guangming Feng, Longfei Han, Yiwen Jia, Peiliang Huang   +3 more
doaj   +1 more source