Image Resampling and Geometrical Transformations
Image resampling is required in many image processing applications. It is a key issue in signal and image differentiating and integrating, image geometrical transformations and re-scaling, target location and tracking with sub-pixel accuracy, Radon Transform and tomographic reconstruction, 3-D image volume rendering and volumetric imaging.
KeywordsGeometrical Transformation Digital Holography Neighbor Interpolation Zero Padding Interpolation Kernel
Unable to display preview. Download preview PDF.
- 1.P. Thévenaz, T. Blu, M. Unser, Image interpolation and resampling, Handbook of Medical Imaging, Processing and Analysis, I. N. Bankman, Ed., Academic Press, San Diego CA, USA, pp. 393–420, 2000Google Scholar
- 2.L.P. Yaroslaysky, Efficient algorithm for discrete sinc-interpolation, Applied Optics, Vol. 36, No.2, 10 January, 1997, p. 460–463Google Scholar
- 3.L. Yaroslaysky, Fast signal sine-interpolation and its applications in signal and image processing, ISandT/SPIE’s 14th Annual Symposium Electronic Imaging 2002, Science and Technology, Conference 4667 “Image Processing: Algorithms and Systems”, San Jose, CA, 21–23 January 2002. Proceedings of SPIE vol. 4667Google Scholar
- 6.J.H. Mathews, K.D. Fink, Numerical methods using MATLAB, Prentice Hall, Inc, 1999Google Scholar
- 8.W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling. Numerical recipes. The art of scientific computing. Cambridge University Press, Cambridge, 1987Google Scholar
- 9.C. Elster, I. Weingärtner, “High-accuracy reconstruction of a function f(x) when only df(x)/dx or d2f(x)/dx2 is known at discrete measurements points”, Proc. SPIE, v. 4782Google Scholar
- 10.L. Yaroslaysky, Y. Chernobrodov, DFT and DCT based Discrete Sinc-interpolation Methods for Direct Fourier Tomographic Reconstruction, 3-d Int. Symposium, Image and Signal Processing and Analysis, Sept. 18–20, 2003, Rome, ItalyGoogle Scholar