Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images.
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| Title: | Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images. |
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| Authors: | Sima, Aleksandra A.1,2 aleksandra.sima@uni.no, Buckley, Simon J.1 simon.buckley@uni.no |
| Source: | Remote Sensing. May2013, Vol. 5 Issue 5, p2037-2056. 20p. 4 Color Photographs, 2 Black and White Photographs, 1 Diagram, 4 Charts, 4 Graphs. |
| Subjects: | Optimizing compilers, Industrial efficiency, Wavelength division multiplexing, Hyperspectral imaging systems, Image registration, Visible spectra, Geometric analysis |
| Abstract: | The scale invariant feature transform (SIFT) is a widely used interest operator for supporting tasks such as 3D matching, 3D scene reconstruction, panorama stitching, image registration and motion tracking. Although SIFT is reported to be robust to disparate radiometric and geometric conditions in visible light imagery, using the default input parameters does not yield satisfactory results when matching imagery acquired at non-overlapping wavelengths. In this paper, optimization of the SIFT parameters for matching multi-wavelength image sets is documented. In order to integrate hyperspectral panoramic images with reference imagery and 3D data, corresponding points were required between visible light and short wave infrared images, each acquired from a slightly different position and with different resolutions and geometric projections. The default SIFT parameters resulted in too few points being found, requiring the influence of five key parameters on the number of matched points to be explored using statistical techniques. Results are discussed for two geological datasets. Using the SIFT operator with optimized parameters and an additional outlier elimination method, allowed between four and 22 times more homologous points to be found with improved image point distributions, than using the default parameter values recommended in the literature [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 89439926 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sima%2C+Aleksandra+A%2E%22">Sima, Aleksandra A.</searchLink><relatesTo>1,2</relatesTo><i> aleksandra.sima@uni.no</i><br /><searchLink fieldCode="AR" term="%22Buckley%2C+Simon+J%2E%22">Buckley, Simon J.</searchLink><relatesTo>1</relatesTo><i> simon.buckley@uni.no</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. May2013, Vol. 5 Issue 5, p2037-2056. 20p. 4 Color Photographs, 2 Black and White Photographs, 1 Diagram, 4 Charts, 4 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Optimizing+compilers%22">Optimizing compilers</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+efficiency%22">Industrial efficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Wavelength+division+multiplexing%22">Wavelength division multiplexing</searchLink><br /><searchLink fieldCode="DE" term="%22Hyperspectral+imaging+systems%22">Hyperspectral imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Image+registration%22">Image registration</searchLink><br /><searchLink fieldCode="DE" term="%22Visible+spectra%22">Visible spectra</searchLink><br /><searchLink fieldCode="DE" term="%22Geometric+analysis%22">Geometric analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The scale invariant feature transform (SIFT) is a widely used interest operator for supporting tasks such as 3D matching, 3D scene reconstruction, panorama stitching, image registration and motion tracking. Although SIFT is reported to be robust to disparate radiometric and geometric conditions in visible light imagery, using the default input parameters does not yield satisfactory results when matching imagery acquired at non-overlapping wavelengths. In this paper, optimization of the SIFT parameters for matching multi-wavelength image sets is documented. In order to integrate hyperspectral panoramic images with reference imagery and 3D data, corresponding points were required between visible light and short wave infrared images, each acquired from a slightly different position and with different resolutions and geometric projections. The default SIFT parameters resulted in too few points being found, requiring the influence of five key parameters on the number of matched points to be explored using statistical techniques. Results are discussed for two geological datasets. Using the SIFT operator with optimized parameters and an additional outlier elimination method, allowed between four and 22 times more homologous points to be found with improved image point distributions, than using the default parameter values recommended in the literature [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs5052037 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 2037 Subjects: – SubjectFull: Optimizing compilers Type: general – SubjectFull: Industrial efficiency Type: general – SubjectFull: Wavelength division multiplexing Type: general – SubjectFull: Hyperspectral imaging systems Type: general – SubjectFull: Image registration Type: general – SubjectFull: Visible spectra Type: general – SubjectFull: Geometric analysis Type: general Titles: – TitleFull: Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sima, Aleksandra A. – PersonEntity: Name: NameFull: Buckley, Simon J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 5 – Type: issue Value: 5 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
