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Fast, Multi-modal and Discontinuity-preserving Image Registration using Mutual Information

Panin, Giorgio (2013) Fast, Multi-modal and Discontinuity-preserving Image Registration using Mutual Information. International Journal on Artificial Intelligence Tools, 22 (06). World Scientific Publishing Co. DOI: 10.1142/S0218213013600154 ISSN 0218-2130

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Official URL: http://www.worldscientific.com/doi/abs/10.1142/S0218213013600154


In this paper, we describe a fast and efficient method for multi-modal and discontinuity-preserving image registration, implemented on graphics hardware. Multi-sensory data fusion and medical image analysis often pose the challenging task of aligning dense, non-rigid and multi-modal images. However, also optical sequences or stereo image pairs may present variable illumination conditions and noise. The above problems can be addressed by an invariant similarity measure, such as mutual information. Additionally, when using a regularized approach to deal with the ill-posedness of the problem, one has to take care of preserving discontinuities at the motion boundaries. Our approach efficiently addresses the above issues through a primal-dual convex estimation framework, using an approximated Hessian matrix that decouples pixel dependencies, while being asymptotically correct. At the same time, we achieve a high computational efficiency by means of pre-quantized kernel density estimation and differentiation, as well as a parallel implementation on the GPU. Our approach is demonstrated on ground-truth data from the Middlebury database, as well as medical and visible-infrared image pairs.

Item URL in elib:https://elib.dlr.de/112567/
Document Type:Article
Title:Fast, Multi-modal and Discontinuity-preserving Image Registration using Mutual Information
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Panin, Giorgiogiorgio.panin (at) dlr.deUNSPECIFIED
Date:December 2013
Journal or Publication Title:International Journal on Artificial Intelligence Tools
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1142/S0218213013600154
Publisher:World Scientific Publishing Co
Keywords:Image registration; multi-modal data; total variation; mutual information; convex optimization; general-purpose GPU computing
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben Multisensorielle Weltmodellierung
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Strobl, Klaus
Deposited On:12 Jun 2017 17:36
Last Modified:08 Mar 2018 18:40

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