A novel control point dispersion method for image registration robust to local distortion

Yuan Yuan; Meng Yu; Lin Lei; Yang Jian; Chen Jingbo; Yue Anzhi; He Dongxu

doi:10.1007/978-3-319-21978-3_25

A novel control point dispersion method for image registration robust to local distortion

Yuan Yuan, Meng Yu, Lin Lei, Yang Jian, Chen Jingbo, Yue Anzhi, He Dongxu

Chinese Academy of Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Extracting well-distributed and precisely aligned control points (CPs) is extremely important for remote sensing image registration, particularly for high resolution images with large local distortion. Based on a theoretical analysis of estimation perturbation in transformation parameters, a novel CP dispersion approach is proposed to select high quality and uniformly distributed CPs. This approach retains a minimum spanning tree (MST) of the selected CPs during the algorithm and adds a new CP to the tree in each iteration until satisfying the convergence condition. Moreover, to acquire adequate number of CPs for the dispersion process, a coarse-to-fine matching approach is proposed. Experiment results indicate that the proposed method improves the match performance compared to other CP dispersion methods in terms of aligning accuracy.

Original language	English
Title of host publication	Image and Graphics - 8th International Conference, ICIG 2015, Proceedings
Editors	Yu-Jin Zhang
Publisher	Springer Verlag
Pages	278-287
Number of pages	10
ISBN (Print)	9783319219776
DOIs	https://doi.org/10.1007/978-3-319-21978-3_25
State	Published - 2015
Externally published	Yes
Event	8th International Conference on Image and Graphics, ICIG 2015 - Tianjin, China Duration: 13 Aug 2015 → 16 Aug 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9217
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Image and Graphics, ICIG 2015
Country/Territory	China
City	Tianjin
Period	13/08/15 → 16/08/15

Keywords

Coarse-to-fine matching strategy
Control point dispersion
Image registration
Local image distortions

Access to Document

10.1007/978-3-319-21978-3_25

Cite this

Yuan, Y., Yu, M., Lei, L., Jian, Y., Jingbo, C., Anzhi, Y., & Dongxu, H. (2015). A novel control point dispersion method for image registration robust to local distortion. In Y.-J. Zhang (Ed.), Image and Graphics - 8th International Conference, ICIG 2015, Proceedings (pp. 278-287). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9217). Springer Verlag. https://doi.org/10.1007/978-3-319-21978-3_25

Yuan, Yuan ; Yu, Meng ; Lei, Lin et al. / A novel control point dispersion method for image registration robust to local distortion. Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. editor / Yu-Jin Zhang. Springer Verlag, 2015. pp. 278-287 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{55eac5c2a71d43208cf3f9a3756b6419,

title = "A novel control point dispersion method for image registration robust to local distortion",

abstract = "Extracting well-distributed and precisely aligned control points (CPs) is extremely important for remote sensing image registration, particularly for high resolution images with large local distortion. Based on a theoretical analysis of estimation perturbation in transformation parameters, a novel CP dispersion approach is proposed to select high quality and uniformly distributed CPs. This approach retains a minimum spanning tree (MST) of the selected CPs during the algorithm and adds a new CP to the tree in each iteration until satisfying the convergence condition. Moreover, to acquire adequate number of CPs for the dispersion process, a coarse-to-fine matching approach is proposed. Experiment results indicate that the proposed method improves the match performance compared to other CP dispersion methods in terms of aligning accuracy.",

keywords = "Coarse-to-fine matching strategy, Control point dispersion, Image registration, Local image distortions",

author = "Yuan Yuan and Meng Yu and Lin Lei and Yang Jian and Chen Jingbo and Yue Anzhi and He Dongxu",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 8th International Conference on Image and Graphics, ICIG 2015 ; Conference date: 13-08-2015 Through 16-08-2015",

year = "2015",

doi = "10.1007/978-3-319-21978-3_25",

language = "英语",

isbn = "9783319219776",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Yuan, Y, Yu, M, Lei, L, Jian, Y, Jingbo, C, Anzhi, Y & Dongxu, H 2015, A novel control point dispersion method for image registration robust to local distortion. in Y-J Zhang (ed.), Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9217, Springer Verlag, pp. 278-287, 8th International Conference on Image and Graphics, ICIG 2015, Tianjin, China, 13/08/15. https://doi.org/10.1007/978-3-319-21978-3_25

A novel control point dispersion method for image registration robust to local distortion. / Yuan, Yuan; Yu, Meng; Lei, Lin et al.
Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. ed. / Yu-Jin Zhang. Springer Verlag, 2015. p. 278-287 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9217).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel control point dispersion method for image registration robust to local distortion

AU - Yuan, Yuan

AU - Yu, Meng

AU - Lei, Lin

AU - Jian, Yang

AU - Jingbo, Chen

AU - Anzhi, Yue

AU - Dongxu, He

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Extracting well-distributed and precisely aligned control points (CPs) is extremely important for remote sensing image registration, particularly for high resolution images with large local distortion. Based on a theoretical analysis of estimation perturbation in transformation parameters, a novel CP dispersion approach is proposed to select high quality and uniformly distributed CPs. This approach retains a minimum spanning tree (MST) of the selected CPs during the algorithm and adds a new CP to the tree in each iteration until satisfying the convergence condition. Moreover, to acquire adequate number of CPs for the dispersion process, a coarse-to-fine matching approach is proposed. Experiment results indicate that the proposed method improves the match performance compared to other CP dispersion methods in terms of aligning accuracy.

AB - Extracting well-distributed and precisely aligned control points (CPs) is extremely important for remote sensing image registration, particularly for high resolution images with large local distortion. Based on a theoretical analysis of estimation perturbation in transformation parameters, a novel CP dispersion approach is proposed to select high quality and uniformly distributed CPs. This approach retains a minimum spanning tree (MST) of the selected CPs during the algorithm and adds a new CP to the tree in each iteration until satisfying the convergence condition. Moreover, to acquire adequate number of CPs for the dispersion process, a coarse-to-fine matching approach is proposed. Experiment results indicate that the proposed method improves the match performance compared to other CP dispersion methods in terms of aligning accuracy.

KW - Coarse-to-fine matching strategy

KW - Control point dispersion

KW - Image registration

KW - Local image distortions

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SN - 9783319219776

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

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EP - 287

BT - Image and Graphics - 8th International Conference, ICIG 2015, Proceedings

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T2 - 8th International Conference on Image and Graphics, ICIG 2015

Y2 - 13 August 2015 through 16 August 2015

ER -

Yuan Y, Yu M, Lei L, Jian Y, Jingbo C, Anzhi Y et al. A novel control point dispersion method for image registration robust to local distortion. In Zhang YJ, editor, Image and Graphics - 8th International Conference, ICIG 2015, Proceedings. Springer Verlag. 2015. p. 278-287. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-21978-3_25

A novel control point dispersion method for image registration robust to local distortion

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