Results 51 to 60 of about 4,335 (202)

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

Image Deblurring Using Multi-Stream Bottom-Top-Bottom Attention Network and Global Information-Based Fusion and Reconstruction Network

Sensors, 2020
Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the ...
Quan Zhou, Mingyue Ding, Xuming Zhang
doaj   +1 more source

Improvement and Assessment of a Blind Image Deblurring Algorithm Based on Independent Component Analysis

Computation, 2021
The aim of the present paper is to improve an existing blind image deblurring algorithm, based on an independent component learning paradigm, by manifold calculus.
Simone Fiori
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

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

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

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

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

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

Progressive deep network for blind motion image deblurring

Xi'an Gongcheng Daxue xuebao, 2023
The multi-stage deep neural network in the blind motion image deblurring task lacks a large range of receptive fields and it was difficult to reasonably interact with the image features of each stage.
WANG Xiaohua, HOU Jiahui, ZHANG Kaibing, CHENG Jing, SU Zebin   +4 more
doaj   +1 more source