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An effective edge-directed frequency filter for removal of aliasing in upsampled images

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Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Konferencja
International Conference on Computer Vision and Graphics ICCVG 2006 (25-27.09.2006 ; Warsaw, Poland)
Języki publikacji
EN
Abstrakty
EN
Raster images can have a range of various distortions related to their raster structure. Their upsampling might in effect substantially reveal the raster structure of the original image, known as aliasing. The upsampling itself may introduce aliasing into the upsampled image as well. The presented method attempts to remove the aliasing using frequency filters based on discrete fast Fourier transform, and applied directionally in certain regions placed along the edges in the image. As opposed to some anisotropic smoothing methods, the presented algorithm aims to selectively reduce the aliasing only, preserving the sharpness of image details. The method can be used as a post-processing filter along with various upsampling algorithms. It was experimentally shown that the method can improve the visual quality of the upsampled images.
Słowa kluczowe
Rocznik
Strony
585--598
Opis fizyczny
Bibliogr. 14 poz., il., wykr.
Twórcy
autor
  • Institute of Theoretical and Applied Computer Science, Bałtycka 5, Gliwice, Poland
Bibliografia
  • [1] Sobel I.: Camera models and machine perception. PhD thesis, Stanford University, USA, 1970.
  • [2] Marr D., Hildreth E. C.: Theory of edge detection. Proc. Royal Soc. London, B 207, pages 187-217, 1980.
  • [3] Keys R.: Bicubic interpolation. IEEE Trans. Acoust. Speech, Signal Processing, 29:1153-1160, 1981.
  • [4] Canny J.: A computational approach to edge detection. IEEE Trans. Pattern Analysis and Machine Intelligence, 8:679-698, 1986.
  • [5] Mitchell D. P., Netravali A. N.: Reconstruction filters in computer graphics. Proc. of the 15th annual conference on Computer graphics and interactive techniques, pages 221 - 228, 1988.
  • [6] Jain A.: Fundamentals of digital image processing. Prentice-Hall, 1989.
  • [7] Perona P., Malik J.: Detecting and localizing edges composed of steps, peaks, and roofs. Technical report, MIT, 1991.
  • [8] Gonzales R. C., Woods R. E.: Digital image processing. Addison Wesley, 1993.
  • [9] Baker S., Nayar S. K., Murase H.: Parametric feature detection. International Journal of of Computer Vision, 27(l):27-50, 1998.
  • [10] Ziou D., Tabbone S.: Edge detection techniques - an overview. International Journal of Pattern Recognition and Image Analysis, 8:537-559, 1998.
  • [11] Xin Li: New edge-directed interpolation. IEEE Transactions on Image Processing, 10(10): 1521-1527, 2001.
  • [12] Martin D., Fowlkes C., Malik J.: Learning to detect natural image boundaries using local brightness, color and texture cues. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(5):530-541, 2002.
  • [13] Tschumperle D., Deriche R.: Vector-valued image regularization with pde's: A common framework for different applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(4):506-517, 2005.
  • [14] Tschumperle D.: Fast anisotropic smoothing of multi-valued images using curvature-preserving pde's. International Journal of Computer Vision, 68(l):65-82, 2006.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA1-0026-0049
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