Results 51 to 60 of about 4,539 (201)

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

Deblurring by Realistic Blurring

, 2020
Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios ...
Li, Hongdong, Liu, Wei, Luo, Wenhan, Ma, Lin, Stenger, Bjorn, Zhang, Kaihao, Zhong, Yiran   +6 more
core   +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

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

Convolutional Deblurring for Natural Imaging

, 2019
In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration.
Hosseini, Mahdi S., Plataniotis, Konstantinos N.   +1 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

A Generalized New Method for Anomalous Phased Array Radar Echo Image Restoration Based on Generative Adversarial Network

Earth and Space Science, Volume 12, Issue 12, December 2025.
Abstract X‐band Phased array radars are characterized by high spatial and temporal resolution, but suffer from a range of data quality problems, such as echo voids after the filtering of ground clutter, abnormal radials, radial obstructions and irregular missing radar echoes. This paper proposes a radar echo image restoration model (GCD) based on color
Jinyan Xu, Ling Yang, Xiaoqiong Zhen, Yan Fu, Zhendong Yao, Chong Wu, Chao Chen   +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

Adversarial Spatio-Temporal Learning for Video Deblurring

, 2018
Camera shake or target movement often leads to undesired blur effects in videos captured by a hand-held camera. Despite significant efforts having been devoted to video-deblur research, two major challenges remain: 1) how to model the spatio-temporal ...
Li, Hongdong, Liu, Wei, Luo, Wenhan, Ma, Lin, Zhang, Kaihao, Zhong, Yiran   +5 more
core   +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