A Pixel-Based Semi-Stochastic Algorithm for the Registration of Geophysical Images.
A Pixel-Based Semi-Stochastic Algorithm for the Registration of Geophysical Images.
The availability of overlapping geophysical data produced by different sensors provides complementary information about the investigation area. However, joint interpretation of these geophysical images is challenging. One common problem is the registration of the images that is necessary to compare features appearing in dissimilar datasets. Measurements in archeological geophysics are often performed by handheld devices therefore, the actual location of the measurement could be different from the planned one. These offsets are localized and essentially random. Consequently, it is impossible to correct them following usual deterministic approaches. This paper presents a novel registration method between geophysical images produced from different prospecting methods. We developed a semi-stochastic, iterative registration algorithm that applies random local transformations in small randomly selected regions of the processed image. The algorithm uses the mutual information of the images as similarity measure due to its suitability in images of different modalities. We use a pair of images to train the algorithm and tune its parameters. Afterwards, we test the method with nine different pairs of geophysical images from various locations and characteristics. The results, in all cases, show a significant increase of the mutual information in comparison with the registration through geographical coordinates.
Registration, Geophysics, Affine Transform, Mutual information
413-424
Karamitrou, Alexandra
25acd266-3030-4958-b5c5-72d4c6b74caf
Tsokas, Gregory N.
5a5bd98b-3bda-476e-95c5-1de677664a49
Petrou, Maria
615c963d-c044-4c9c-9897-2e72b6dc2ebf
1 September 2017
Karamitrou, Alexandra
25acd266-3030-4958-b5c5-72d4c6b74caf
Tsokas, Gregory N.
5a5bd98b-3bda-476e-95c5-1de677664a49
Petrou, Maria
615c963d-c044-4c9c-9897-2e72b6dc2ebf
Karamitrou, Alexandra, Tsokas, Gregory N. and Petrou, Maria
(2017)
A Pixel-Based Semi-Stochastic Algorithm for the Registration of Geophysical Images.
Archaeological Prospection, 24, , [10.1002/arp.1578].
(doi:10.1002/arp.1578).
Abstract
The availability of overlapping geophysical data produced by different sensors provides complementary information about the investigation area. However, joint interpretation of these geophysical images is challenging. One common problem is the registration of the images that is necessary to compare features appearing in dissimilar datasets. Measurements in archeological geophysics are often performed by handheld devices therefore, the actual location of the measurement could be different from the planned one. These offsets are localized and essentially random. Consequently, it is impossible to correct them following usual deterministic approaches. This paper presents a novel registration method between geophysical images produced from different prospecting methods. We developed a semi-stochastic, iterative registration algorithm that applies random local transformations in small randomly selected regions of the processed image. The algorithm uses the mutual information of the images as similarity measure due to its suitability in images of different modalities. We use a pair of images to train the algorithm and tune its parameters. Afterwards, we test the method with nine different pairs of geophysical images from various locations and characteristics. The results, in all cases, show a significant increase of the mutual information in comparison with the registration through geographical coordinates.
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More information
Accepted/In Press date: 8 May 2017
e-pub ahead of print date: 12 July 2017
Published date: 1 September 2017
Additional Information:
Copyright © 2017 John Wiley & Sons, Ltd.
Keywords:
Registration, Geophysics, Affine Transform, Mutual information
Identifiers
Local EPrints ID: 458156
URI: http://eprints.soton.ac.uk/id/eprint/458156
ISSN: 1075-2196
PURE UUID: 1e8b50ed-2060-4849-979e-de00938ac60c
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Date deposited: 29 Jun 2022 17:23
Last modified: 17 Mar 2024 04:00
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Contributors
Author:
Alexandra Karamitrou
Author:
Gregory N. Tsokas
Author:
Maria Petrou
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