Structure-from-motion, multi-view stereo photogrammetry applied to line-scan sediment core images
Images of sediment cores are often acquired to preserve primary color information, before such profiles are altered by subsequent sampling and destructive analyses. In many cases, however, no post-processing of these images is undertaken to extract information, despite the fact that image processing...
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description | Images of sediment cores are often acquired to preserve primary color information, before such profiles are altered by subsequent sampling and destructive analyses. In many cases, however, no post-processing of these images is undertaken to extract information, despite the fact that image processing can be used to describe and measure structures within the sample. Improvements of RGB (Red/Green/Blue) cameras and image processing algorithms now enable acquisition of high-resolution, metrically calibrated pictures called ortho-images, which have great potential. The way to obtain such ortho-images is by processing several raw images. We propose a semi-automated method that uses metrically calibrated targets to create the ortho-image, using Agisoft Photoscan software and a Python script. The method was tested on sediment cores up to 1.5 m long. It was compared to an approach without markers, one that uses only image matching. The proposed method showed better resolution and less distortion (GSD: 59 µm, RMSE: 7–18 µm). Images acquired without calibrated targets can still be used, by manually positioning points that can then be metrically calibrated. This approach is very useful for smartphone images taken in the field. There are many potential applications for such images of sediment cores, for instance as metric stratigraphic logs to facilitate description of the profile by unit, to study and measure structures (e.g. laminae, instantaneous deposits), or use of image registration or data fusion to create spatial landmarks for non-destructive sensors or destructive laboratory analyses. High-resolution metrically calibrated RGB images of sediment cores are simple to acquire and can play an important role in paleoclimate and paleoenvironmental studies. |
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In many cases, however, no post-processing of these images is undertaken to extract information, despite the fact that image processing can be used to describe and measure structures within the sample. Improvements of RGB (Red/Green/Blue) cameras and image processing algorithms now enable acquisition of high-resolution, metrically calibrated pictures called ortho-images, which have great potential. The way to obtain such ortho-images is by processing several raw images. We propose a semi-automated method that uses metrically calibrated targets to create the ortho-image, using Agisoft Photoscan software and a Python script. The method was tested on sediment cores up to 1.5 m long. It was compared to an approach without markers, one that uses only image matching. The proposed method showed better resolution and less distortion (GSD: 59 µm, RMSE: 7–18 µm). Images acquired without calibrated targets can still be used, by manually positioning points that can then be metrically calibrated. This approach is very useful for smartphone images taken in the field. There are many potential applications for such images of sediment cores, for instance as metric stratigraphic logs to facilitate description of the profile by unit, to study and measure structures (e.g. laminae, instantaneous deposits), or use of image registration or data fusion to create spatial landmarks for non-destructive sensors or destructive laboratory analyses. High-resolution metrically calibrated RGB images of sediment cores are simple to acquire and can play an important role in paleoclimate and paleoenvironmental studies.</description><identifier>ISSN: 0921-2728</identifier><identifier>EISSN: 1573-0417</identifier><identifier>DOI: 10.1007/s10933-021-00204-x</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Algorithms ; Calibration ; Cameras ; Climate Change ; Color imagery ; Colour ; Cores ; Data integration ; Earth and Environmental Science ; Earth Sciences ; Engineering Sciences ; Environmental Engineering ; Environmental Sciences ; Freshwater & Marine Ecology ; Geology ; High resolution ; Image acquisition ; Image processing ; Image registration ; Image resolution ; Information processing ; Laminates ; Multisensor fusion ; Original Paper ; Paleoclimate ; Paleontology ; Photogrammetry ; Physical Geography ; Post-production processing ; Programming languages ; Resolution ; Sciences of the Universe ; Sediment ; Sedimentology ; Sediments ; Signal and Image processing ; Smartphones ; Stratigraphy ; Target acquisition</subject><ispartof>Journal of paleolimnology, 2021-10, Vol.66 (3), p.249-260</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a420t-d2b4e78d7e4397918c50d38d0a383b978b6680b7b6bf91076aa47ccf968de8033</citedby><cites>FETCH-LOGICAL-a420t-d2b4e78d7e4397918c50d38d0a383b978b6680b7b6bf91076aa47ccf968de8033</cites><orcidid>0000-0002-3991-2184 ; 0000-0001-6586-3083 ; 0000-0003-4411-8898 ; 0000-0002-0693-7959 ; 0000-0001-8258-4545</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10933-021-00204-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10933-021-00204-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://sde.hal.science/hal-03257581$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Jacq, Kévin</creatorcontrib><creatorcontrib>Ployon, Estelle</creatorcontrib><creatorcontrib>Rapuc, William</creatorcontrib><creatorcontrib>Blanchet, Claire</creatorcontrib><creatorcontrib>Pignol, Cécile</creatorcontrib><creatorcontrib>Coquin, Didier</creatorcontrib><creatorcontrib>Fanget, Bernard</creatorcontrib><title>Structure-from-motion, multi-view stereo photogrammetry applied to line-scan sediment core images</title><title>Journal of paleolimnology</title><addtitle>J Paleolimnol</addtitle><description>Images of sediment cores are often acquired to preserve primary color information, before such profiles are altered by subsequent sampling and destructive analyses. In many cases, however, no post-processing of these images is undertaken to extract information, despite the fact that image processing can be used to describe and measure structures within the sample. Improvements of RGB (Red/Green/Blue) cameras and image processing algorithms now enable acquisition of high-resolution, metrically calibrated pictures called ortho-images, which have great potential. The way to obtain such ortho-images is by processing several raw images. We propose a semi-automated method that uses metrically calibrated targets to create the ortho-image, using Agisoft Photoscan software and a Python script. The method was tested on sediment cores up to 1.5 m long. It was compared to an approach without markers, one that uses only image matching. The proposed method showed better resolution and less distortion (GSD: 59 µm, RMSE: 7–18 µm). Images acquired without calibrated targets can still be used, by manually positioning points that can then be metrically calibrated. This approach is very useful for smartphone images taken in the field. There are many potential applications for such images of sediment cores, for instance as metric stratigraphic logs to facilitate description of the profile by unit, to study and measure structures (e.g. laminae, instantaneous deposits), or use of image registration or data fusion to create spatial landmarks for non-destructive sensors or destructive laboratory analyses. High-resolution metrically calibrated RGB images of sediment cores are simple to acquire and can play an important role in paleoclimate and paleoenvironmental studies.</description><subject>Algorithms</subject><subject>Calibration</subject><subject>Cameras</subject><subject>Climate Change</subject><subject>Color imagery</subject><subject>Colour</subject><subject>Cores</subject><subject>Data integration</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Engineering Sciences</subject><subject>Environmental Engineering</subject><subject>Environmental Sciences</subject><subject>Freshwater & Marine Ecology</subject><subject>Geology</subject><subject>High resolution</subject><subject>Image acquisition</subject><subject>Image processing</subject><subject>Image registration</subject><subject>Image resolution</subject><subject>Information processing</subject><subject>Laminates</subject><subject>Multisensor fusion</subject><subject>Original 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multi-view stereo photogrammetry applied to line-scan sediment core images</title><author>Jacq, Kévin ; Ployon, Estelle ; Rapuc, William ; Blanchet, Claire ; Pignol, Cécile ; Coquin, Didier ; Fanget, Bernard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a420t-d2b4e78d7e4397918c50d38d0a383b978b6680b7b6bf91076aa47ccf968de8033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Calibration</topic><topic>Cameras</topic><topic>Climate Change</topic><topic>Color imagery</topic><topic>Colour</topic><topic>Cores</topic><topic>Data integration</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Engineering Sciences</topic><topic>Environmental Engineering</topic><topic>Environmental Sciences</topic><topic>Freshwater & Marine Ecology</topic><topic>Geology</topic><topic>High resolution</topic><topic>Image 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subjects | Algorithms Calibration Cameras Climate Change Color imagery Colour Cores Data integration Earth and Environmental Science Earth Sciences Engineering Sciences Environmental Engineering Environmental Sciences Freshwater & Marine Ecology Geology High resolution Image acquisition Image processing Image registration Image resolution Information processing Laminates Multisensor fusion Original Paper Paleoclimate Paleontology Photogrammetry Physical Geography Post-production processing Programming languages Resolution Sciences of the Universe Sediment Sedimentology Sediments Signal and Image processing Smartphones Stratigraphy Target acquisition |
title | Structure-from-motion, multi-view stereo photogrammetry applied to line-scan sediment core images |
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