Minimizing Seam Lines in UAV Multispectral Image Mosaics Utilizing Irradiance, Vignette, and BRDF.
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| Title: | Minimizing Seam Lines in UAV Multispectral Image Mosaics Utilizing Irradiance, Vignette, and BRDF. |
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| Authors: | Ahn, Hoyong1 (AUTHOR) hyahn85@korea.kr, Kim, Chansol2 (AUTHOR) kcs4464@pukyong.ac.kr, Lim, Seungchan2 (AUTHOR) sc6888@pukyong.ac.kr, Jin, Cheonggil2 (AUTHOR) cgjin@pukyong.ac.kr, Kim, Jinsu2 (AUTHOR) jinsookim@pknu.ac.kr, Choi, Chuluong2 (AUTHOR) cuchoi@pknu.ac.kr |
| Source: | Remote Sensing. Jan2025, Vol. 17 Issue 1, p151. 19p. |
| Subjects: | Aerial photography, Drone aircraft, Radiance, Vignettes, Reflectance |
| Abstract: | Unmanned aerial vehicle (UAV) imaging provides the ability to obtain high-resolution images at a lower cost than satellite imagery and aerial photography. However, multiple UAV images need to be mosaicked to obtain images of large areas, and the resulting UAV multispectral image mosaics typically contain seam lines. To address this problem, we applied irradiance, vignette, and bidirectional reflectance distribution function (BRDF) filters and performed field work using a DJI Mavic 3 Multispectral (M3M) camera to collect data. We installed a calibrated reference tarp (CRT) in the center of the collection area and conducted three types of flights (BRDF, vignette, and validation) to measure the irradiance, radiance, and reflectance—which are essential for irradiance correction—using a custom reflectance box (ROX). A vignette filter was generated from the vignette parameter, and the anisotropy factor (ANIF) was calculated by measuring the radiance at the nadir, following which the BRDF model parameters were calculated. The calibration approaches were divided into the following categories: a vignette-only process, which solely applied vignette and irradiance corrections, and the full process, which included irradiance, vignette, and BRDF. The accuracy was verified through a validation flight. The radiance uncertainty at the seam line ranged from 3.00 to 5.26% in the 80% lap mode when using nine images around the CRT, and from 4.06 to 6.93% in the 50% lap mode when using all images with the CRT. The term 'lap' in 'lap mode' refers to both overlap and sidelap. The images that were subjected to the vignette-only process had a radiance difference of 4.48–6.98%, while that of the full process images was 1.44–2.40%, indicating that the seam lines were difficult to find with the naked eye and that the process was successful. [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.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 182446208 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Minimizing Seam Lines in UAV Multispectral Image Mosaics Utilizing Irradiance, Vignette, and BRDF. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ahn%2C+Hoyong%22">Ahn, Hoyong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hyahn85@korea.kr</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Chansol%22">Kim, Chansol</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> kcs4464@pukyong.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Lim%2C+Seungchan%22">Lim, Seungchan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> sc6888@pukyong.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Jin%2C+Cheonggil%22">Jin, Cheonggil</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> cgjin@pukyong.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Jinsu%22">Kim, Jinsu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jinsookim@pknu.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Choi%2C+Chuluong%22">Choi, Chuluong</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> cuchoi@pknu.ac.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jan2025, Vol. 17 Issue 1, p151. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Aerial+photography%22">Aerial photography</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+aircraft%22">Drone aircraft</searchLink><br /><searchLink fieldCode="DE" term="%22Radiance%22">Radiance</searchLink><br /><searchLink fieldCode="DE" term="%22Vignettes%22">Vignettes</searchLink><br /><searchLink fieldCode="DE" term="%22Reflectance%22">Reflectance</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Unmanned aerial vehicle (UAV) imaging provides the ability to obtain high-resolution images at a lower cost than satellite imagery and aerial photography. However, multiple UAV images need to be mosaicked to obtain images of large areas, and the resulting UAV multispectral image mosaics typically contain seam lines. To address this problem, we applied irradiance, vignette, and bidirectional reflectance distribution function (BRDF) filters and performed field work using a DJI Mavic 3 Multispectral (M3M) camera to collect data. We installed a calibrated reference tarp (CRT) in the center of the collection area and conducted three types of flights (BRDF, vignette, and validation) to measure the irradiance, radiance, and reflectance—which are essential for irradiance correction—using a custom reflectance box (ROX). A vignette filter was generated from the vignette parameter, and the anisotropy factor (ANIF) was calculated by measuring the radiance at the nadir, following which the BRDF model parameters were calculated. The calibration approaches were divided into the following categories: a vignette-only process, which solely applied vignette and irradiance corrections, and the full process, which included irradiance, vignette, and BRDF. The accuracy was verified through a validation flight. The radiance uncertainty at the seam line ranged from 3.00 to 5.26% in the 80% lap mode when using nine images around the CRT, and from 4.06 to 6.93% in the 50% lap mode when using all images with the CRT. The term 'lap' in 'lap mode' refers to both overlap and sidelap. The images that were subjected to the vignette-only process had a radiance difference of 4.48–6.98%, while that of the full process images was 1.44–2.40%, indicating that the seam lines were difficult to find with the naked eye and that the process was successful. [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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=182446208 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs17010151 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 151 Subjects: – SubjectFull: Aerial photography Type: general – SubjectFull: Drone aircraft Type: general – SubjectFull: Radiance Type: general – SubjectFull: Vignettes Type: general – SubjectFull: Reflectance Type: general Titles: – TitleFull: Minimizing Seam Lines in UAV Multispectral Image Mosaics Utilizing Irradiance, Vignette, and BRDF. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ahn, Hoyong – PersonEntity: Name: NameFull: Kim, Chansol – PersonEntity: Name: NameFull: Lim, Seungchan – PersonEntity: Name: NameFull: Jin, Cheonggil – PersonEntity: Name: NameFull: Kim, Jinsu – PersonEntity: Name: NameFull: Choi, Chuluong IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 17 – Type: issue Value: 1 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
