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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Geometric Calibration of a Hyperspectral Frame Camera

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Author(s):
de Oliveira, Raquel A. ; Tommaselli, Antonio M. G. ; Honkavaara, Eija
Total Authors: 3
Document type: Journal article
Source: PHOTOGRAMMETRIC RECORD; v. 31, n. 155, p. 325-347, SEP 2016.
Web of Science Citations: 10
Abstract

Recently, miniaturised hyperspectral sensors operable from small unmanned airborne vehicle platforms have entered the market. The emerging hyperspectral imaging technologies, based on frame cameras and tuneable filters, are attractive alternatives to hyperspectral pushbroom sensors. This paper addresses the geometric calibration process of a hyperspectral frame camera based on a Fabry-Perot interferometer. However, the addition of more optical elements in front of the image sensor can affect the parameters related to the internal geometry of the camera, and a deficiency in knowledge regarding these parameters can have a critical effect on the accuracy of 3D measurements in photogrammetric applications. The experiments focused on assessing the self-calibrating bundle adjustment to verify the behaviour of the interior parameters, considering different spectral bands. The results indicated that the applied self-calibration method can accurately characterise the interior parameters of this camera and that one set of parameters is required for each internal sensor. (AU)

FAPESP's process: 13/50426-4 - Unmanned airborne vehicle-based 4D remote sensing for mapping Rain Forest biodiversity and its change in Brazil (UAV_4D_Bio)
Grantee:Antonio Maria Garcia Tommaselli
Support type: Regular Research Grants
FAPESP's process: 13/17787-3 - DEVELOPMENT AND ASSESSMENT OF TECHNIQUES FOR GENERATION OF DENSE POINTS CLOUD USING HYPERSPECTRAL IMAGES ACQUIRED BY UAV
Grantee:Raquel Alves de Oliveira
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 14/24844-6 - Generation of DSM based on segmentation and classification of hyperspectral image
Grantee:Raquel Alves de Oliveira
Support type: Scholarships abroad - Research Internship - Doctorate