Results 51 to 60 of about 4,574 (198)

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

A Noise-Robust Blind Deblurring Algorithm With Wavelet-Enhanced Diffusion Model for Optical Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Blind deblurring of optical remote sensing images has been a longstanding challenge. In recent years, many learning-based deblurring algorithms have been greatly developed.
Zhiyuan Li, Jie Li, Yueting Zhang, Jiayi Guo, Yirong Wu   +4 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

Blind Remote Sensing Image Deblurring Based on Local Maximum High-Frequency Coefficient Prior and Graph Regularization

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In satellite remote sensing imaging, factors such as optical axis shift, image plane jitter, movement of the target object, and Earth's rotation can induce image blur.
Zhidan Cai, Ming Fang, Zhe Li, Jinyi Ming, Huimin Wang   +4 more
doaj   +1 more source

Enhancing convolutional neural network generalizability via low‐rank weight approximation

IET Image Processing, Volume 20, Issue 1, January/December 2026.
A self‐supervised framework is proposed for image denoising based on the Tucker low‐rank tensor approximation. With the proposed design, we are able to characterize our denoiser with fewer parameters and train it based on a single image, which considerably improves the model's generalizability and reduces the cost of data acquisition. Abstract Noise is
Chenyin Gao, Shu Yang, Anru R. Zhang
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   +2 more sources

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, Pan, Jinshan, Ren, Wenqi, Yang, Ming-Hsuan   +3 more
core   +1 more source

Diffusion Models and Its Applications in Image Dehazing: A Survey

IET Image Processing, Volume 20, Issue 1, January/December 2026.
1.This survey represents the first systematic and comprehensive overview of diffusion model‐based image dehazing, aiming to provide a valuable guide for future researchers and stimulate continued progress in this field. 2.We summarize relevant papers along with their corresponding code links and other resources for image dehazing and all‐in‐one image ...
Liangyu Zhu, Yanzhao Su, Zhigao Cui, Yunwei Lan, Nian Wang, Lanqing Zhang, Yanping Cai   +6 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