Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

Georgios Karagiannis, Francesc/François Antón Castro, Darka Mioc

Research output: Contribution to journalConference articleResearchpeer-review

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Abstract

An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detected are invariant to image rotations, translations, scaling and also to changes in illumination, brightness and 3-dimensional viewpoint. Afterwards, each feature of the reference image is matched with one in the sensed image if, and only if, the distance between them multiplied by a threshold is shorter than the distances between the point and all the other points in the sensed image. Then, the matched features are used to compute the parameters of the homography that transforms the coordinate system of the sensed image to the coordinate system of the reference image. The Delaunay triangulations of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches.

Conference

Conference23rd Congress of the International Society of Photogrammetry and Remote Sensing
Number23
CountryCzech Republic
CityPrague
Period12/07/201619/07/2016
Internet address

Keywords

  • Automated image matching
  • SIFT algorithm
  • Delaunay triangulation
  • Graph isomorphism
  • Multi-sensor image matching
  • Multi-temporal image matching

Cite this

@inproceedings{dd5b6b5a40dc4f7ba3c4ec2c44472a91,
title = "Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation",
abstract = "An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detected are invariant to image rotations, translations, scaling and also to changes in illumination, brightness and 3-dimensional viewpoint. Afterwards, each feature of the reference image is matched with one in the sensed image if, and only if, the distance between them multiplied by a threshold is shorter than the distances between the point and all the other points in the sensed image. Then, the matched features are used to compute the parameters of the homography that transforms the coordinate system of the sensed image to the coordinate system of the reference image. The Delaunay triangulations of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches.",
keywords = "Automated image matching, SIFT algorithm, Delaunay triangulation, Graph isomorphism, Multi-sensor image matching, Multi-temporal image matching",
author = "Georgios Karagiannis and {Ant{\'o}n Castro}, Francesc/Fran{\cc}ois and Darka Mioc",
year = "2016",
doi = "10.5194/isprs-annals-III-2-23-2016",
language = "English",
volume = "III-2",
pages = "23--28",
journal = "I S P R S Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences",
issn = "2194-9042",
publisher = "Copernicus GmbH",

}

Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation. / Karagiannis, Georgios ; Antón Castro, Francesc/François; Mioc, Darka.

In: I S P R S Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. III-2, 2016, p. 23-28.

Research output: Contribution to journalConference articleResearchpeer-review

TY - GEN

T1 - Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

AU - Karagiannis, Georgios

AU - Antón Castro, Francesc/François

AU - Mioc, Darka

PY - 2016

Y1 - 2016

N2 - An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detected are invariant to image rotations, translations, scaling and also to changes in illumination, brightness and 3-dimensional viewpoint. Afterwards, each feature of the reference image is matched with one in the sensed image if, and only if, the distance between them multiplied by a threshold is shorter than the distances between the point and all the other points in the sensed image. Then, the matched features are used to compute the parameters of the homography that transforms the coordinate system of the sensed image to the coordinate system of the reference image. The Delaunay triangulations of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches.

AB - An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detected are invariant to image rotations, translations, scaling and also to changes in illumination, brightness and 3-dimensional viewpoint. Afterwards, each feature of the reference image is matched with one in the sensed image if, and only if, the distance between them multiplied by a threshold is shorter than the distances between the point and all the other points in the sensed image. Then, the matched features are used to compute the parameters of the homography that transforms the coordinate system of the sensed image to the coordinate system of the reference image. The Delaunay triangulations of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches.

KW - Automated image matching

KW - SIFT algorithm

KW - Delaunay triangulation

KW - Graph isomorphism

KW - Multi-sensor image matching

KW - Multi-temporal image matching

U2 - 10.5194/isprs-annals-III-2-23-2016

DO - 10.5194/isprs-annals-III-2-23-2016

M3 - Conference article

VL - III-2

SP - 23

EP - 28

JO - I S P R S Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

JF - I S P R S Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

SN - 2194-9042

ER -