Structure adaptive anisotropic filtering for magnetic resonance image enhancement
This paper presents a structure adaptive anisotropic filtering method and its applications. It differs from other techniques in that instead of using local gradient as a means of controlling the anisotropism of the filters, it uses the local intensity orientation of level contours and its curvature to control the shape and the extent of the filter kernel. This ensures that edges and corners are well preserved throughout the filtering process.
Unable to display preview. Download preview PDF.
- 1.J.S. Lee, “Digital image enhancement and noise filtering by use of local statistics,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-2(2), pp. 165–168, 1980.Google Scholar
- 2.D.C. Wang, A.H. Vagucci, and C.C. Li, “Gradient inverse weighted scheme and the evaluation of its performance,” Computer Graphics and Image Processing, vol. 15, pp. 167–181, 1981.Google Scholar
- 3.X. Wang, “On the gradient inverse weighted filter,” IEEE Transactions on Signal Processing, vol. 40(2), pp. 482–484, 1992.Google Scholar
- 4.G.A. Mastin, “Adaptive filters for digital image noise smoothing: an evaluation,” Computer Vision, Graphics, and Image Processing, vol. 31, pp. 103–121, 1985.Google Scholar
- 5.P. Perona and J. Malik, “Scale-space and edge detection using anisotropic diffusion,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, pp. 629–639, 1990.Google Scholar
- 6.G. Gerig, O. Kübier, R. Kikinis and F.A. Jolesz, “Nonlinear anisotropic filtering of MRI data,” IEEE Transactions on Medical Imaging, vol. 11, pp. 221–232, 1992.Google Scholar
- 7.J. Bigün and H. Granlund, “Optimal orientation detection of linear symmetry,” Proc. of the First International Conference on Computer Vision, pp. 433–438, 1987, London.Google Scholar
- 8.R. Bracewell, The Fourier Transform and Its Applications, McGraw-Hill, New York, 1965.Google Scholar
- 9.G.Z. Yang and P. Burger, “Optimal extraction of image flow from spatiotemporal images,” Imperial College Research Report, DOC 90/9, 1990, University of London.Google Scholar