ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2023, Vol. 20, No. 4, pp. 45-59

Transformation of images captured by ultra-wide-angle lenses

V.A. Grishin 1 , N.A. Stroilov 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 04.07.2023
DOI: 10.21046/2070-7401-2023-20-4-45-59
In various application areas (navigation systems, video recorders, surveillance systems, etc.), cameras with wide-angle or ultra-wide-angle lenses are used. Such cameras allow you to get an image in a wide viewing angle. Even for visual analysis, the captured images are not always suitable due to the presence of significant geometric distortions. For this reason, the captured images are subjected to special correction (transformation) to reduce these distortions. The situation becomes even more complicated if images obtained from ultra-wide-angle cameras need to be used to solve recognition and/or measurement problems. Moreover, in many cases it is advisable to transform the images obtained from such cameras to the usual model of the central projection. In the process of such a transformation, it becomes necessary to use the interpolation of brightness over a non-uniform grid of samples. Interpolation is necessary because in the process of correcting geometric distortions, the sample grid of the original image becomes sparse and does not form a dense coverage on the plane where the transformed image is projected. This effect leads to the need to use brightness interpolation. Although after such transformations the image is visually perceived as having no defects, however, in fact, the quality of the images deteriorates, which can affect the operation of recognition and/or measurement algorithms. Using a specific example, the article shows how significant distortions in the brightness of images can be with such a transformation.
Keywords: ultra-wide-angle lenses, fish-eye lenses, image transformation, image interpolation distortion
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References:

  1. Alyautdinov A. R., Koshel S. M., Geometric transformation of digital cartographic data by reference points, In: Kartograficheskii metod i vozmozhnosti komp’yuternykh sistem (Cartographic method and possibilities of computer systems), Berlyant A. M., Paslavski Ya. A. (eds.), Warsaw, 2001, pp. 93–97 (in Russian).
  2. Dolgal A. S., Kostitsyn V. I., Novikova P. N., Pugin A. V., Rashidov V. A., Khristenko L. A., Practical application of sourcewise approximation geological and geophysical data, Geofizika, 2017, No. 5, pp. 29–37 (in Russian).
  3. Zhuravlev A. V., Zhuravlev V. M., A Multidimensional Algorithm for Linear Interpolation with Smoothing on a Simplex Coverage of a Domain with an Arbitrary Distribution of Irregular Grid Nodes, Izvestiya vysshikh uchebnykh zavedenii, Povolzhskii region, Fiziko-matematicheskie nauki, Fizika, 2007, No. 4, pp. 93–104 (in Russian).
  4. Lazarenko V. P., Djamiykov T. S., Korotaev V. V., Yaryshev S. N., Transformation algorithm for images obtained by omnidirectional cameras, Scientific and Technical J. Information Technologies, Mechanics and Optics, 2015, Vol. 15, No. 1, pp. 30–39 (in Russian), DOI: 10.17586/2226-1494-2015-15-1-30-39.
  5. Amidror I., Scattered data interpolation methods for electronic imaging systems: a survey, J. Electronic Imaging, 2002, Vol. 11, Issue 2, pp. 157–176, DOI: 10.1117/1.1455013.
  6. Basso K., De Avila Zingano P. R., Dal Sasso Freitas C. M., Interpolation of Scattered Data: Investigating Alternatives for the Modified Shepard Method, Proc. 12 th Brazilian Symp. Computer Graphics and Image Processing, Campinas, Brazil, 1999, Cat. No. PR00481, pp. 39–47, DOI: 10.1109/SIBGRA.1999.805606.
  7. Dell’Accio F., Di Tommaso F., Scattered data interpolation by Shepard’s like methods: classical results and recent advances, Proc. Kernel-based Methods and Function Approximation, Dolomites Research Notes on Approximation, 2016, Vol. 9, pp. 32–44.
  8. Franke R., Scattered Data Interpolation: Tests of Some Method, Mathematics of Computation, 1982, Vol. 38, No. 157, pp. 181–200, DOI: 10.2307/2007474.
  9. Iñiguez A., Improving Image Resolution with Wide-Angle Lenses, A&S Intern., Jan. 2014, pp. 48–54, https://media.theiatech.com/documents/theia-whitepaper-improve-resolution-wide-angle-lens.pdf.
  10. Masjukov A. V., Masjukov V. V., A New Fast Iterative Method for Interpolation of Multivariate Scattered Data, Computational Methods in Applied Mathematics, 2005, Vol. 5, No. 3, pp. 276–293.
  11. Peterson M., Eliminate Distortion in Wide Angle Images, Theia Technologies, 2008, 3 p., https://media.theiatech.com/documents/theia-whitepaper-eliminate-distortion-in-wide-angle-lenses.pdf.
  12. Renka R. J., Multivariate Interpolation of Large Sets of Scattered Data, ACM Trans. Mathematical Software, 1988, Vol. 14, No. 2, pp. 139–148, DOI: 10.1145/45054.45055.
  13. Vlachkova K., Radev K. A., Comparative Study of Methods for Scattered Data Interpolation Using Minimum Norm Networks and Quartic Triangular Bézier Surfaces, Proc. Information Systems and Grid Technologies Workshop, ISGT’2022, May 27–28, 2022, Sofia, Bulgaria, 2022, pp. 159–169.