Impact of Light Spectrum on Photogrammetric Feature Localization
Playlist
  • light spectrum
  • key point localisation
  • photogrammetry
  • demosaicing
  • greyscale
Chapter
00:11
Author's Biography
00:40
Introduction
01:07
Purpose of the Study
01:26
Methodology
02:01
Results
02:36
Conclusions
Video Introduction

This video is adapted from 10.3390/rs16142644

In modern digital photogrammetry, an image is usually registered via a digital matrix with an array of colour filters. From the registration of the image until feature points are detected on the image, the image is subjected to a series of calculations, i.e., demosaicing and conversion to greyscale, among others. These algorithms respond differently to the varying light spectrum of the scene, which consequently results in the feature location changing. In this research, the effect of scene illumination on the localisation of a feature in an image is presented. The demosaicing and greyscale conversion algorithms that produce the largest and smallest deviation of the feature from the reference point were assessed. Twelve different illumination settings from polychromatic light to monochromatic light were developed and performed, and five different demosaicing algorithms and five different methods of converting a colour image to greyscale were analysed. A total of 300 different cases were examined. As the study shows, the lowest deviation in the polychromatic light domain was achieved for light with a colour temperature of 5600 K and 5000 K, while in the monochromatic light domain, it was achieved for light with a green colour. Demosaicing methods have a significant effect on the localisation of a feature, and so the smallest feature deviation was achieved for smooth hue-type demosaicing, while for greyscale conversion, it was achieved for the mean type. Demosaicing and greyscale conversion methods for monochrome light had no effect. The research discusses the problem and concludes with recommendations and suggestions in the area of illuminating the scene with artificial light and the application of the algorithms, in order to achieve the highest accuracy using photogrammetric methods.

 

(1) Paweł Burdziakowski - Google Scholar. https://scholar.google.pl/citations?user=xC6mTPsAAAAJ&hl=pl.

(2) Paweł Burdziakowski, Ph.D., from the Department of Geodesy has received funding ..... https://wilis.pg.edu.pl/kg/2023-02/dr-inz-pawel-burdziakowski-z-katedry-geodezji-otrzymal-dofinansowanie-na-realizacje-projektu-w-ramach-grantu-neptunium.

(3) Pawel Burdziakowski - Biography - MOST Knowledge. https://mostwiedzy.pl/pl/pawel-burdziakowski,1009666-1/bio.

(4) Pawel Burdziakowski - Scientific profile - MOST Knowledge. https://mostwiedzy.pl/pl/pawel-burdziakowski,1009666-1.

(5) Pawel Burdziakowski. https://sciprofiles.com/profile/621428.

(6) https://doi.org/10.3390/app122412851.

(7) https://doi.org/10.1080/23248378.2022.2140713.

(8) https://doi.org/10.3390/en15114094.

(9) https://doi.org/10.3390/s22051723.

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If you have any further questions, please contact Encyclopedia Editorial Office.
Burdziakowski, P. Impact of Light Spectrum on Photogrammetric Feature Localization. Encyclopedia. Available online: https://encyclopedia.pub/video/video_detail/1355 (accessed on 13 October 2024).
Burdziakowski P. Impact of Light Spectrum on Photogrammetric Feature Localization. Encyclopedia. Available at: https://encyclopedia.pub/video/video_detail/1355. Accessed October 13, 2024.
Burdziakowski, Pawel. "Impact of Light Spectrum on Photogrammetric Feature Localization" Encyclopedia, https://encyclopedia.pub/video/video_detail/1355 (accessed October 13, 2024).
Burdziakowski, P. (2024, September 10). Impact of Light Spectrum on Photogrammetric Feature Localization. In Encyclopedia. https://encyclopedia.pub/video/video_detail/1355
Burdziakowski, Pawel. "Impact of Light Spectrum on Photogrammetric Feature Localization." Encyclopedia. Web. 10 September, 2024.
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