First Order Locally Orderless Registration

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Standard

First Order Locally Orderless Registration. / Darkner, Sune; Vidarte, José D.T.; Lauze, François.

Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings. ed. / Abderrahim Elmoataz; Jalal Fadili; Yvain Quéau; Julien Rabin; Loïc Simon. Springer, 2021. p. 177-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12679 LNCS).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Harvard

Darkner, S, Vidarte, JDT & Lauze, F 2021, First Order Locally Orderless Registration. in A Elmoataz, J Fadili, Y Quéau, J Rabin & L Simon (eds), Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12679 LNCS, pp. 177-188, 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021, Virtual, Online, 16/05/2021. https://doi.org/10.1007/978-3-030-75549-2_15

APA

Darkner, S., Vidarte, J. D. T., & Lauze, F. (2021). First Order Locally Orderless Registration. In A. Elmoataz, J. Fadili, Y. Quéau, J. Rabin, & L. Simon (Eds.), Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings (pp. 177-188). Springer. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12679 LNCS https://doi.org/10.1007/978-3-030-75549-2_15

Vancouver

Darkner S, Vidarte JDT, Lauze F. First Order Locally Orderless Registration. In Elmoataz A, Fadili J, Quéau Y, Rabin J, Simon L, editors, Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings. Springer. 2021. p. 177-188. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12679 LNCS). https://doi.org/10.1007/978-3-030-75549-2_15

Author

Darkner, Sune ; Vidarte, José D.T. ; Lauze, François. / First Order Locally Orderless Registration. Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings. editor / Abderrahim Elmoataz ; Jalal Fadili ; Yvain Quéau ; Julien Rabin ; Loïc Simon. Springer, 2021. pp. 177-188 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12679 LNCS).

Bibtex

@inproceedings{5217ab0466ad4898a09c8c06780e3794,
title = "First Order Locally Orderless Registration",
abstract = "First Order Locally Orderless Registration (FLOR) is a scale-space framework for image density estimation used for defining image similarity, mainly for Image Registration. The Locally Orderless Registration framework was designed in principle to use zeroth-order information, providing image density estimates over three scales: image scale, intensity scale, and integration scale. We extend it to take first-order information into account and hint at higher-order information. We show how standard similarity measures extend into the framework. We study especially Sum of Squared Differences (SSD) and Normalized Cross-Correlation (NCC) but present the theory of how Normalised Mutual Information (NMI) can be included.",
keywords = "First order information, Image registration, Locally Orderless Images",
author = "Sune Darkner and Vidarte, {Jos{\'e} D.T.} and Fran{\c c}ois Lauze",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021 ; Conference date: 16-05-2021 Through 20-05-2021",
year = "2021",
doi = "10.1007/978-3-030-75549-2_15",
language = "English",
isbn = "9783030755485",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "177--188",
editor = "Abderrahim Elmoataz and Jalal Fadili and Yvain Qu{\'e}au and Julien Rabin and Lo{\"i}c Simon",
booktitle = "Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings",
address = "Switzerland",

}

RIS

TY - GEN

T1 - First Order Locally Orderless Registration

AU - Darkner, Sune

AU - Vidarte, José D.T.

AU - Lauze, François

N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.

PY - 2021

Y1 - 2021

N2 - First Order Locally Orderless Registration (FLOR) is a scale-space framework for image density estimation used for defining image similarity, mainly for Image Registration. The Locally Orderless Registration framework was designed in principle to use zeroth-order information, providing image density estimates over three scales: image scale, intensity scale, and integration scale. We extend it to take first-order information into account and hint at higher-order information. We show how standard similarity measures extend into the framework. We study especially Sum of Squared Differences (SSD) and Normalized Cross-Correlation (NCC) but present the theory of how Normalised Mutual Information (NMI) can be included.

AB - First Order Locally Orderless Registration (FLOR) is a scale-space framework for image density estimation used for defining image similarity, mainly for Image Registration. The Locally Orderless Registration framework was designed in principle to use zeroth-order information, providing image density estimates over three scales: image scale, intensity scale, and integration scale. We extend it to take first-order information into account and hint at higher-order information. We show how standard similarity measures extend into the framework. We study especially Sum of Squared Differences (SSD) and Normalized Cross-Correlation (NCC) but present the theory of how Normalised Mutual Information (NMI) can be included.

KW - First order information

KW - Image registration

KW - Locally Orderless Images

U2 - 10.1007/978-3-030-75549-2_15

DO - 10.1007/978-3-030-75549-2_15

M3 - Article in proceedings

AN - SCOPUS:85106402902

SN - 9783030755485

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 177

EP - 188

BT - Scale Space and Variational Methods in Computer Vision - 8th International Conference, SSVM 2021, Proceedings

A2 - Elmoataz, Abderrahim

A2 - Fadili, Jalal

A2 - Quéau, Yvain

A2 - Rabin, Julien

A2 - Simon, Loïc

PB - Springer

T2 - 8th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2021

Y2 - 16 May 2021 through 20 May 2021

ER -

ID: 283137220