Iterative gradient-based shift estimation: To multiscale or not to multiscale?

Martin RAIS; Jean-Michel MOREL; Gabriele FACCIOLO

doi:10.1007/978-3-319-25751-8_50

Iterative gradient-based shift estimation: To multiscale or not to multiscale?

Martin RAIS^*
, Jean-Michel MOREL
, Gabriele FACCIOLO

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

2 Citations (Scopus)

Abstract

Fast global shift estimation is a critical preprocessing step on many high level tasks such as remote sensing or medical imaging. In this work we deal with a simple question: should we use an iterative technique to perform shift estimation or should we use a multiscale approach. Based on the obtained results, both methodologies proved to lose accuracy as the noise increases, however this accuracy loss increases with the shift magnitude. The conclusion is that a multiscale strategy should be used when the shift magnitude is higher than approximately a fifth of a pixel.

Original language	English
Title of host publication	Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 20th Iberoamerican Congress, CIARP 2015, Proceedings
Editors	Alvaro PARDO, Josef KITTLER
Publisher	Springer, Cham
Pages	416-423
Number of pages	8
ISBN (Electronic)	9783319257518
ISBN (Print)	9783319257501
DOIs	https://doi.org/10.1007/978-3-319-25751-8_50
Publication status	Published - 2015
Externally published	Yes
Event	20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015 - Montevideo, Uruguay Duration: 9 Nov 2015 → 12 Nov 2015

Publication series

Name	Lecture Notes in Computer Science
Volume	9423
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015
Country/Territory	Uruguay
City	Montevideo
Period	9/11/15 → 12/11/15

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Funding

During this work, the author had a fellowship of the Ministerio de Economia y Competividad (Spain), reference BES-2012-057113, for the realization of his Ph.D. thesis. This work was also partially supported by the Centre National d’Etudes Spatiales (MISS Project), the European Research Council (Advanced Grant Twelve Labours), the Office of Naval Research (under Grant N00014-97-1-0839), Direction Générale de l’Armement, Fondation Mathématique Jacques Hadamard and Agence Nationale de la Recherche (Stereo project).

Keywords

Iterative
Multiscale
Shift estimation

Access to Document

10.1007/978-3-319-25751-8_50

Cite this

RAIS, M., MOREL, J.-M., & FACCIOLO, G. (2015). Iterative gradient-based shift estimation: To multiscale or not to multiscale? In A. PARDO, & J. KITTLER (Eds.), Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 20th Iberoamerican Congress, CIARP 2015, Proceedings (pp. 416-423). (Lecture Notes in Computer Science; Vol. 9423). Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_50

RAIS, Martin ; MOREL, Jean-Michel ; FACCIOLO, Gabriele. / Iterative gradient-based shift estimation: To multiscale or not to multiscale?. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 20th Iberoamerican Congress, CIARP 2015, Proceedings. editor / Alvaro PARDO ; Josef KITTLER. Springer, Cham, 2015. pp. 416-423 (Lecture Notes in Computer Science).

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title = "Iterative gradient-based shift estimation: To multiscale or not to multiscale?",

abstract = "Fast global shift estimation is a critical preprocessing step on many high level tasks such as remote sensing or medical imaging. In this work we deal with a simple question: should we use an iterative technique to perform shift estimation or should we use a multiscale approach. Based on the obtained results, both methodologies proved to lose accuracy as the noise increases, however this accuracy loss increases with the shift magnitude. The conclusion is that a multiscale strategy should be used when the shift magnitude is higher than approximately a fifth of a pixel.",

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author = "Martin RAIS and Jean-Michel MOREL and Gabriele FACCIOLO",

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RAIS, M, MOREL, J-M & FACCIOLO, G 2015, Iterative gradient-based shift estimation: To multiscale or not to multiscale? in A PARDO & J KITTLER (eds), Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 20th Iberoamerican Congress, CIARP 2015, Proceedings. Lecture Notes in Computer Science, vol. 9423, Springer, Cham, pp. 416-423, 20th Iberoamerican Congress on on Pattern Recognition, CIARP 2015, Montevideo, Uruguay, 9/11/15. https://doi.org/10.1007/978-3-319-25751-8_50

Iterative gradient-based shift estimation: To multiscale or not to multiscale? / RAIS, Martin; MOREL, Jean-Michel; FACCIOLO, Gabriele.
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 20th Iberoamerican Congress, CIARP 2015, Proceedings. ed. / Alvaro PARDO; Josef KITTLER. Springer, Cham, 2015. p. 416-423 (Lecture Notes in Computer Science; Vol. 9423).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review