Results 31 to 40 of about 4,574 (198)

A two‐step image stabilisation method for promoting visual quality in vision‐enabled maritime surveillance systems

IET Intelligent Transport Systems, 2023
Maritime surveillance systems have been commonly exploited in vessel traffic services. The maritime visual information can be obtained through shore‐borne, ship‐borne or air‐borne cameras. However, the obtained visual data often suffers from blur effects
Yanhong Huang, Ryan Wen Liu, Jingxian Liu   +2 more
doaj   +1 more source

Blind Image Deblurring In The Edge Domain [PDF]

, 2004
Publication in the conference proceedings of EUSIPCO, Viena, Austria ...
COLONNESE, Stefania, CAMPISI P., PANCI G., SCARANO, Gaetano   +3 more
openaire   +4 more sources

Blind image deblurring method based on l₁/l₂-norm regularization

Journal of Measurement Science and Instrumentation, 2023
Aiming at the problem of ringing artifacts existing in the edge of image in traditional blind image deblurring methods, l1/l2 regularization-based blind image deblurring method is proposed. The latent image is constrained by l1/l2 regularization, and the
CAO Shengfang, HU Hongping, WANG Wenke
doaj  

Reference-Based Multi-Level Features Fusion Deblurring Network for Optical Remote Sensing Images

Remote Sensing, 2022
Blind image deblurring is a long-standing challenge in remote sensing image restoration tasks. It aims to recover a latent sharp image from a blurry image while the blur kernel is unknown.
Zhiyuan Li, Jiayi Guo, Yueting Zhang, Jie Li, Yirong Wu   +4 more
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

Fast and easy blind deblurring using an inverse filter and PROBE

, 2017
PROBE (Progressive Removal of Blur Residual) is a recursive framework for blind deblurring. Using the elementary modified inverse filter at its core, PROBE's experimental performance meets or exceeds the state of the art, both visually and quantitatively.
J Kotera, L Bar, L Xu, N Komodakis, Q Shan, R Fergus, R Hanocka, S Osher, TF Chan, WZ Shao, Y Zhou, YL You   +11 more
core   +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

Blind Image Deblurring via a Novel Sparse Channel Prior

Mathematics, 2022
Blind image deblurring (BID) is a long-standing challenging problem in low-level image processing. To achieve visually pleasing results, it is of utmost importance to select good image priors. In this work, we develop the ratio of the dark channel prior (
Dayi Yang, Xiaojun Wu, Hefeng Yin
doaj   +1 more source

Blind Image Deblurring via Reweighted Graph Total Variation

, 2017
Blind image deblurring, i.e., deblurring without knowledge of the blur kernel, is a highly ill-posed problem. The problem can be solved in two parts: i) estimate a blur kernel from the blurry image, and ii) given estimated blur kernel, de-convolve blurry
Bai, Yuanchao, Cheung, Gene, Gao, Wen, Liu, Xianming   +3 more
core   +1 more source

Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal [PDF]

, 2015
In this paper, we address the problem of estimating and removing non-uniform motion blur from a single blurry image. We propose a deep learning approach to predicting the probabilistic distribution of motion blur at the patch level using a convolutional ...
Cao, Wenfei, Ponce, Jean, Sun, Jian, Xu, Zongben   +3 more
core   +5 more sources