Saved in:
Bibliographic Details
Main Authors: Jain, Tushar, Lubien, Madeline, Gilles, Jerome
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.20816
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914993361911808
author Jain, Tushar
Lubien, Madeline
Gilles, Jerome
author_facet Jain, Tushar
Lubien, Madeline
Gilles, Jerome
contents A variety of neural networks architectures are being studied to tackle blur in images and videos caused by a non-steady camera and objects being captured. In this paper, we present an overview of these existing networks and perform experiments to remove the blur caused by atmospheric turbulence. Our experiments aim to examine the reusability of existing networks and identify desirable aspects of the architecture in a system that is geared specifically towards atmospheric turbulence mitigation. We compare five different architectures, including a network trained in an end-to-end fashion, thereby removing the need for a stabilization step.
format Preprint
id arxiv_https___arxiv_org_abs_2410_20816
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Evaluation of neural network algorithms for atmospheric turbulence mitigation
Jain, Tushar
Lubien, Madeline
Gilles, Jerome
Computer Vision and Pattern Recognition
A variety of neural networks architectures are being studied to tackle blur in images and videos caused by a non-steady camera and objects being captured. In this paper, we present an overview of these existing networks and perform experiments to remove the blur caused by atmospheric turbulence. Our experiments aim to examine the reusability of existing networks and identify desirable aspects of the architecture in a system that is geared specifically towards atmospheric turbulence mitigation. We compare five different architectures, including a network trained in an end-to-end fashion, thereby removing the need for a stabilization step.
title Evaluation of neural network algorithms for atmospheric turbulence mitigation
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2410.20816