Physics of Wave Processes and Radio SystemsPhysics of Wave Processes and Radio Systems1810-31892782-294XPovolzhskiy State University of Telecommunications and Informatics869710.18469/1810-3189.2021.24.1.58-66Research ArticleImproving noise immunity of homography superposition for television signalsDiyazitdinovaAlfiya A.<p>head of the Research Department, Povolzhskiy State University of Telecommunications and Informatics, Samara, Russia.</p>
<p><em>Research interests</em>: computer signal processing, television signals superposition, television signals parameters estimation, object’s recognition at machine vision.</p>a.miftahova@psuti.ruhttps://orcid.org/0000-0001-8940-4543Povolzhskiy State University of Telecommunications and Informatics06052021241586606052021Copyright © 2021, Diyazitdinova A.A.2021<p>The algorithm of homography superposition of the television signals was shown in this article. The algorithm allows improving noise immunity for homography parameters of television signal with textural fragments. The core of the estimation procedure of homography parameters for image superposition is the matching of the feature points. The feature points are local extremes of the pixel brightness of the image. The matching is defined by the maximum correlation coefficient between a region of the image of a neighbor area of the feature point. The log-polar system of the images provides an invariant correlation of scale and rotate are proportional offsets along the axis in this coordinate system. The noise immunity is provided due to the developing procedure of removing feature points in the textural region. This procedure leads to decreasing probability of error matching of the feature points. The numerical modeling shows high noise immunity of the developed procedure in comparing the current researches.</p>noise immunityhomographysuperpositiontelevisionlog-polarfeature pointmatchingпомехоустойчивостьпроективныйсовмещениетелевизионныйлогарифмически полярныйособая точкасопоставления[Goshin E.V., Kotov A.P., Fursov V.A. Two-step spatial transform shaping for aligning images. Komp’juternaja optika, 2014, vol. 38, no. 4, pp. 886–891. DOI: https://doi.org/10.18287/0134-2452-2014-38-4-886-891 (In Russ.)][Novikov A.I. et al. The contour analysis and image-superimposition problem in computer vision systems. Pattern Recognition and Image Analysis, 2015, vol. 25, no. 1, pp. 73–80. DOI: https://doi.org/10.1134/S1054661815010149][Hast A., Nysjö J., Marchetti A. Optimal RANSAC – Towards a repeatable algorithm for finding the optimal set. Journal of WSCG, 2013, vol. 21, no. 1, pp. 21–30.][Efimov A.I., Novikov A.I. Algorithm for step-by-step refinement of projective transformation for image alignment. Komp’juternaja optika, 2016, vol. 40, no. 2, pp. 258–265. DOI: https://doi.org/10.18287/2412-6179-2016-40-2-258-265 (In Russ.)][Loeckx D. et al. Nonrigid image registration using free-form deformations with a local rigidity constraint. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. Lecture Notes in Computer Science, 2004, vol. 3216, pp. 639–646. DOI: https://doi.org/10.1007/978-3-540-30135-6_78][Ke Y., Sukthankar R. PCA-SIFT: A more distinctive representation for local image descriptors. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004, vol. 2, pp. 506–513. DOI: https://doi.org/10.1109/CVPR.2004.1315206][Gruzman I.S. et al. Digital Image Processing in Information Systems. Novosibirsk: Izd-vo NGTU, 2002, 351 p. (In Russ.)][Kulyas O.L. et al. Measurement of characteristics and assessment of the capabilities of cameras with ultra-wide angle optics. Physics of Wave Processes and Radio Systems, 2020, vol. 23, no. 1, pp. 89–99. DOI: https://doi.org/10.18469/1810-3189.2020.23.1.89-99 (In Russ.)][Harris С., Stephens M. A combined corner and edge detector. Proceedings of the Alvey Vision Conference, 1988, pp. 147–151. DOI: https://doi.org/10.5244/C.2.23][Mjasnikov E.V. Determination of parameters of geometric transformations for blending portrait images. Komp’juternaja optika, 2007, vol. 31, no. 3, pp. 77–82. URL: http://www.computeroptics.smr.ru/KO/Annot/KO31-3/14.html (In Russ.)]