A detector of structural similarity for multi-modal microscopic image registration

This paper presents a Detector of Structural Similarity (DSS) to minimize the visual differences between brightfield and confocal microscopic images. The context of this work is that it is very challenging to effectively register such images due to a low structural similarity in image contents. To a...

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Bibliographic Details
Published in:Multimedia tools and applications 2018-03, Vol.77 (6), p.7675-7701
Main Authors: Lv, Guohua, Teng, Shyh Wei, Lu, Guojun
Format: Article
Language:English
Subjects:
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Image registration
Multimedia Information Systems
Registration
Similarity
Special Purpose and Application-Based Systems
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Summary:This paper presents a Detector of Structural Similarity (DSS) to minimize the visual differences between brightfield and confocal microscopic images. The context of this work is that it is very challenging to effectively register such images due to a low structural similarity in image contents. To address this issue, DSS aims to maximize the structural similarity by utilizing the intensity relationships among red-green-blue (RGB) channels in images. Technically, DSS can be combined with any multi-modal image registration technique in registering brightfield and confocal microscopic images. Our experimental results show that DSS significantly increases the visual similarity in such images, thereby improving the registration performance of an existing state-of-the-art multi-modal image registration technique by up to approximately 27%.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-017-4669-y