TY - JOUR

T1 - Thermal IR imaging

T2 - 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications

AU - Sledz, A.

AU - Unger, J.

AU - Heipke, C.

PY - 2018/9/26

Y1 - 2018/9/26

N2 - This paper deals with two aspects of photogrammetric processing of thermal images: image quality and 3D reconstruction quality. The first aspect of the paper relates to the influence of day light on Thermal InfraRed (TIR) images captured by an Unmanned Aerial Vehicle (UAV). Environmental factors such as ambient temperature and lack of sun light affect TIR image quality. We acquire image sequences of the same object during day and night and compare the generated orthophotos according to different metrics like contrast and signal-to-noise ratio (SNR). Our experiments show that performing TIR image acquisition during night time provides a better thermal contrast, regardless of whether we compute contrast over the whole image or over small patches. The second aspect investigated in this work is the potential of using TIR images for photogrammetric tasks such as the automatic generation of Digital Surface Models (DSM) and orthophotos. Due to the low geometrical resolution of a TIR camera and the low image quality in terms of contrast and noise compared to RGB images, the TIR DSM suffers from reconstruction errors and an orthophoto generated using the TIR DSM and TIR images is visibly influenced by those errors. We therefore include measurements of the UAVs positions during image capturing provided by a Global Navigation Satellite System (GNSS) receiver to retrieve position and orientation of TIR and RGB images in the same world coordinate system. To generate an orthophoto from TIR images, they are projected onto the DSM reconstructed from RGB images. This procedure leads to a TIR orthophoto of much higher quality in terms of geometrical correctness.

AB - This paper deals with two aspects of photogrammetric processing of thermal images: image quality and 3D reconstruction quality. The first aspect of the paper relates to the influence of day light on Thermal InfraRed (TIR) images captured by an Unmanned Aerial Vehicle (UAV). Environmental factors such as ambient temperature and lack of sun light affect TIR image quality. We acquire image sequences of the same object during day and night and compare the generated orthophotos according to different metrics like contrast and signal-to-noise ratio (SNR). Our experiments show that performing TIR image acquisition during night time provides a better thermal contrast, regardless of whether we compute contrast over the whole image or over small patches. The second aspect investigated in this work is the potential of using TIR images for photogrammetric tasks such as the automatic generation of Digital Surface Models (DSM) and orthophotos. Due to the low geometrical resolution of a TIR camera and the low image quality in terms of contrast and noise compared to RGB images, the TIR DSM suffers from reconstruction errors and an orthophoto generated using the TIR DSM and TIR images is visibly influenced by those errors. We therefore include measurements of the UAVs positions during image capturing provided by a Global Navigation Satellite System (GNSS) receiver to retrieve position and orientation of TIR and RGB images in the same world coordinate system. To generate an orthophoto from TIR images, they are projected onto the DSM reconstructed from RGB images. This procedure leads to a TIR orthophoto of much higher quality in terms of geometrical correctness.

KW - Photogrammetry

KW - Thermal Infrared Imaging

KW - UAV

UR - http://www.scopus.com/inward/record.url?scp=85056163930&partnerID=8YFLogxK

U2 - 10.5194/isprs-archives-XLII-1-413-2018

DO - 10.5194/isprs-archives-XLII-1-413-2018

M3 - Conference article

AN - SCOPUS:85056163930

VL - 42

SP - 413

EP - 420

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

SN - 1682-1750

IS - 1

Y2 - 10 October 2018 through 12 October 2018

ER -