350 rub
Journal Achievements of Modern Radioelectronics №9 for 2011 г.
Article in number:
Method of construction of compound curve to the restoration boundaries of objects in images
Authors:
V.V. Voronin, V.I. Marchuk, G.R. Saakian
Abstract:
An automated restoration of the areas with the lost pixels is it one of problem of image processing. This problem is particularly acute in the implementation of automatic processing of two-dimensional signals from the CCD in digital cameras and machine vision. The paper presents a new method for reconstruction of two-dimensional signals based on the construction of a composite curve for the restoration of the boundaries of the image, which uses the concept of parametric and geometric continuity. It is shown that this method allows you to recover the curved contours in the region with missing pixels using the approximation of boundaries of objects cubic splines. Suggested that after the restoration of the boundary of objects using the method of image reconstruction by the synthesis of texture and structure, which is to find similar blocks in the original image and copying them into the area with missing pixels.
Pages: 11-15
References
  1. Bertalmio M., Bertozzi A., Sapiro G. Fluid dynamics, and image and video inpainting // Hawaii: Proc. IEEE Computer Vision and Pattern Recognition(CVPR). 2001.Р. 213-226.
  2. Perona P., Malik J. Scale-space and edge detection using anisotropic diffusion // IEEE Transactions on Pattern Analysis and Machine Intelligence. 1990. V. 12(7). P. 629-639.
  3. Alkachouh Z., Bellanger M.G. Fast DCT-based spatial domain interpolation of blocks in images // IEEE Trans. Image Process.2000.V. 9. № 4. Р. 729-732.
  4. Elad M., Starck J., Querre P., and Donoho D. Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA) // Applied and Computational Harmonic Analysis. 2005.V. 19. № 3. Р. 340-358.
  5. Criminisi A., Perez P., Toyama K. Region filling and object removal by exemplar-based image inpainting // IEEE Trans. Image Process.2004.V. 13(9). P. 28-34.
  6. Bertalmio M., Vese L., Sapiro G., Osher S. Simultaneous texture and structure image inpainting // Proceedings of the International Conference on Computer Vision and Pattern Recognition. 2003. Р. 707-712.
  7. Погорелов А.В. Дифференциальная геометрия. М.: Наука. 1974.
  8. Херн Д., Бейкер М.П. Компьютерная графика и стандарт OpenGL. Изд. 3-е: пер. с англ. М.: Издательский дом «Вильямс». 2005.
  9. Шикин Е.В., Боресков А.В. Компьютерная графика. Динамика, реалистичные изображения. М.: ДИАЛОГ-МИФИ. 1995.
  10. Шикин Е.В., Франк-Каменецкий М.М. Кривые на плоскости и в пространстве. М.: ФАЗИС. 1997.
  11. Bartels R.H., Beatty J.C., Brain A.B. Introduction to splines in computer graphics and geometric modeling. Morgan Kaufmann Publishers. Inc. 1995.
  12. Voronin, V.V., Marchuk, V.I., Egiazarian, K.O. Images reconstruction using modified exemplar based method // In Image Processing: Algorithms and Systems IX, edited by Jaakko T. Astola, Karen O. Egiazarian. Proceedings of SPIE V. 7870 (SPIE, Bellingham, WA 2011) 78700N.
  13. Марчук В.И., Воронин В.В., Шерстобитов А.И. Метод восстановления значений двумерных сигналов на основе синтеза текстуры и структуры изображений // Электротехнические и информационные комплексы и системы: научно-технический и теоретический журнал. М.: РГУТиС. 2010. № 2. Т. 6. С. 25-33.
  14. Марчук В.И., Воронин В.В., Франц В.А. Модифицированный метод восстановления двумерных сигналов // Научно-технические ведомости СПбГПУ. Санкт-Петербург: 2011. № 1. С. 31-36.