The photogrammetric processing of thermal infrared (TIR) images deals with several difficulties. TIR images ordinarily have low-resolution and the contrast of the images is very low. These factors strongly complicate the photogrammetric processing, especially when a modern structure from motion method is used. These factors can be avoided by a certain co-processing method of TIR and RGB images. Two of the solutions of co-processing were suggested by the authors and are presented in this article. Each solution requires a different type of transformation-plane transformation and spatial transformation. Both types of transformations are discussed in this paper. On the experiments that were performed, there are presented requirements, advantages, disadvantages, and results of the transformations. Both methods are evaluated mainly in terms of accuracy. The transformations are presented on suggested methods, but they can be easily applied to different kinds of methods of co-processing of TIR and RGB images.

Department of Geomatics Faculty of Civil Engineering Czech Technical University Prague 16629 Prague Czech Republic

EuroGV Spol s r o 11000 Prague Czech Republic

Zobrazit více v PubMed

Capel D., Zisserman A. Computer vision applied to super resolution. IEEE Signal Process. Mag. 2003;20:75–86. doi: 10.1109/MSP.2003.1203211. DOI

Wakeford Z.E., Chmielewska M., Hole M.J., Howell J.A., Jerram D.A. Combining thermal imaging with photogrammetry of an active volcano using UAV: An example from Stromboli, Italy. Photogramm. Rec. 2019;34:445–466. doi: 10.1111/phor.12301. DOI

Sledz A., Unger J., Heipke C. Thermal IR imaging: Image quality and orthophoto generation. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2018;42:413–420. doi: 10.5194/isprs-archives-XLII-1-413-2018. DOI

Maset E., Fusiello A., Crosilla F., Toldo R., Zorzetto D. Photogrammetric 3D building reconstruction from thermal images. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2017;4:25–32. doi: 10.5194/isprs-annals-IV-2-W3-25-2017. DOI

Grechi G., Fiorucci M., Marmoni G.M., Martino S. 3D Thermal Monitoring of Jointed Rock Masses through Infrared Thermography and Photogrammetry. Remote Sens. 2021;13:957. doi: 10.3390/rs13050957. DOI

Hoegner L., Tuttas S., Xu Y., Eder K., Stilla U. Evaluation of methods for coregistration and fusion of rpas-based 3d point clouds and thermal infrared images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2016;41:241–246. doi: 10.5194/isprs-archives-XLI-B3-241-2016. DOI

Weber I., Jenal A., Kneer C., Bongartz J. PANTIR-a dual camera setup for precise georeferencing and mosaicing of thermal aerial images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2015;40:269–272. doi: 10.5194/isprsarchives-XL-3-W2-269-2015. DOI

Adamopoulos E., Volinia M., Girotto M., Rinaudo F. Three-Dimensional Thermal Mapping from IRT Images for Rapid Architectural Heritage NDT. Buildings. 2020;10:187. doi: 10.3390/buildings10100187. DOI

Javadnejad F., Gillins D.T., Parrish C.E., Slocum R.K. A photogrammetric approach to fusing natural colour and thermal infrared UAS imagery in 3D point cloud generation. Int. J. Remote Sens. 2020;41:211–237. doi: 10.1080/01431161.2019.1641241. DOI

Dlesk A., Vach K. Point Cloud Generation of a Building from Close Range Thermal Images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2019;42:29–33. doi: 10.5194/isprs-archives-XLII-5-W2-29-2019. DOI

Acorsi M.G., Gimenez L.M., Martello M. Assessing the Performance of a Low-Cost Thermal Camera in Proximal and Aerial Conditions. Remote Sens. 2020;12:3591. doi: 10.3390/rs12213591. DOI

Šedina J., Housarová E., Raeva P. Using RPAS for the detection of archaeological objects using multispectral and thermal imaging. Eur. J. Remote Sens. 2019;52:182–191. doi: 10.1080/22797254.2018.1562848. DOI

Řehák M., Pavelka K. Using of uav for photogrammetry and thermal imaging; Proceedings of the 33nd Asian Conference on Remote Sensing, ACRS2012, CD-Proceedings; Pattaya, Thailand. 26–30 November 2012.

Luhmann T., Robson S., Kyle S., Harley I. Close Range Photogrammetry. Principles, Techniques and Applications. Whittles Publishing; Scotland, UK: 2011. pp. 448–458.

User’s Manual FLIR Exx Series. [(accessed on 26 April 2021)]; Available online: https://www.flir.com/globalassets/imported-assets/document/flir-exx-series-user-manual.pdf.

Fluke: Thermal Cameras. [(accessed on 26 April 2021)]; Available online: https://www.fluke.com/en-in/products/thermal-cameras.

The Engineering ToolBox: Emissivity Coefficient Materials. [(accessed on 7 June 2021)]; Available online: https://www.engineeringtoolbox.com/emissivity-coefficients-d_447.html.

Usamentiaga R., Garcia D.F., Ibarra-Castanedo C., Maldague X. Highly accurate geometric calibration for infrared cameras using inexpensive calibration targets. Measurement. 2017;112:105–116. doi: 10.1016/j.measurement.2017.08.027. DOI

Remondino F., Fraser C. Digital camera calibration methods: Considerations and comparisons. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2016;36:266–272.

Luhmann T., Piechel J., Roelfs T. Geometric calibration of thermographic cameras. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2010;38:411–416.

Förstner W., Wrobel B.P. Photogrammetric Computer Vision. Springer International Publishing; Cham, Switzerland: 2016. pp. 696–707.

Sanz-Ablanedo E., Chandler J.H., Wackrow R. Parameterising internal camera geometry with focusing distance. Photogramm. Rec. 2012;27:210–226. doi: 10.1111/j.1477-9730.2012.00677.x. DOI

Clarke T.A., Wang X., Fryer J.G. The principal point and CCD cameras. Photogramm. Rec. 1998;16:293–312. doi: 10.1111/0031-868X.00127. DOI

Photogrammetric Co-Processing of Thermal Infrared Images and RGB Images