УДК: 004.932.2
Digital stabilization of images under conditions of planned movement
Full text «Opticheskii Zhurnal»
Full text on elibrary.ru
Publication in Journal of Optical Technology
Званцев С.П., Иванов П.И., Мерзлютин Е.Ю. Цифровая стабилизация изображений в условиях запланированного движения // Оптический журнал. 2012. Т. 79. № 11. С. 59–66.
Zvantsev S. P., Ivanov P. I., Merzlyutin E. Yu. Digital stabilization of images under conditions of planned movement [in English] // Opticheskii Zhurnal. 2012. V. 79. № 11. P. 59–66.
S. P. Zvantsev, P. I. Ivanov, and E. Yu. Merzlyutin, "Digital stabilization of images under conditions of planned movement," Journal of Optical Technology. 79(11), 721-726 (2012). https://doi.org/10.1364/JOT.79.000721
This paper discusses aspects of the solution of the image-stabilization problem, using pictures taken by a movable camera to improve the operator’s perception of the images of a scene when the size of the scene exceeds the size of the visualization region. Methods are proposed of increasing the selection quality of pairs of points for estimating the parameters of the actual and planned movement of the image of the scene. An approach to the implementation of the algorithm in real time is discussed.
digital image stabilization, movable base, evaluation of motion parameters
OCIS codes: 100.2960
References:1. J. Yang and D. Schonfeld, “Robust video stabilization based on particle filter tracking of projected camera motion,” IEEE Trans. Circuits Syst. Video Technol. 19, 945 (2009).
2. C. T. Lin and C. T. Hong, “Real-time digital image-stabilization system using modified proportional integrated controller,” IEEE Trans. Circuits Syst. Video Technol. 19, 427 (2009).
3. T. B. Terriberry, L. M. French, and J. Helmsen, “GPU accelerating speeded-up robust features,” in Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT’08), Atlanta, Georgia, June 2008, pp. 355–362.
4. Z. Pan and C.-W. Ngo, “Selective object stabilization for home video consumers,” IEEE Trans. Consum. Electron. 51, 248 (2005).
5. A. Litvin and J. Konrad, “Probabilistic video stabilization using Kalman filtering and mosaicking,” Proc. SPIE 5022, 663 (2003).
6. Z. Duric and A. Rosenfeld, “Shooting a smooth video with a shaky camera,” Mach. Vis. Appl. 13, 303 (2003).
7. S. Ert¨urk, “Real-time digital image stabilization using Kalman filters,” Real-Time Imag. 8, 317 (2002).
8. H. Bay, T. Tuytelaars, and L. Van Gool, “SURF: Speeded up robust features,” in European Conference on Computer Vision, Vol. 1, 2006, pp. 404–417.
9. G. De Haan, P. W. A. Biezen, H. Huijgen, and O. A. Ojo, “True motion estimation with 3-D recursive search block matching,” IEEE Trans. Circuits Syst. Video Technol. 3, No. 6, 248 (1993).
10. D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” Int. J. Comput. Vis. 60, No. 2, 91 (2004).
11. A. N. Kanatnikov and A. P. Krishchenko, Mathematics in a Technical University. Issue IV: Linear Algebra (Izd. MGTU im. Baumana, Moscow, 2002), p. 296.
12. S. A. Soldatov, K. N. Strel’nikov, and D. S. Vatolin, “Rapid and reliable determination of the global movement in video sequences,” in Transactions of Conference Graphicon—2006, 2006, pp. 430–437.