Unified functional framework for restoration of image sequences degraded by atmospheric turbulence

Naftali Zon, Nahum Kiryati

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We propose a unified functional to address the restoration of turbulence-degraded images. This functional quantifies the association between a given image sequence and a candidate latent image restoration. Minimizing the functional using the alternating direction method of multipliers (ADMM) and Moreau proximity mapping leads to a general algorithmic flow. We show that various known algorithms can be derived as special cases of the general approach. Furthermore, we show that building-blocks used in turbulence recovery algorithms, such as optical flow estimation and blind deblurring, are called for by the general model. The main contribution of this work is the establishment of a unified theoretical framework for the restoration of turbulence-degraded images. It leads to novel turbulence recovery algorithms as well as to better understanding of known ones.

Original languageEnglish
Title of host publicationEnergy Minimization Methods in Computer Vision and Pattern Recognition - 11th International Conference, EMMCVPR 2017, Revised Selected Papers
EditorsMarcello Pelillo, Edwin Hancock
PublisherSpringer Verlag
Pages205-219
Number of pages15
ISBN (Print)9783319781983
DOIs
StatePublished - 2018
Event11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMVCPR 2017 - Venice, Italy
Duration: 30 Oct 20171 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10746 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMVCPR 2017
Country/TerritoryItaly
CityVenice
Period30/10/171/11/17

Fingerprint

Dive into the research topics of 'Unified functional framework for restoration of image sequences degraded by atmospheric turbulence'. Together they form a unique fingerprint.

Cite this