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Issue No.02 - March/April (2008 vol.14)
pp: 289-301
In this paper prefiltered reconstruction techniquesare evaluated for volume-rendering applications. All the analyzedmethods perform a discrete prefiltering as a preprocessing of theinput samples in order to improve the quality of the continuousreconstruction afterwards. Various prefiltering schemes havebeen proposed to fulfill either spatial-domain or frequencydomaincriteria. According to our best knowledge, however, theirthorough comparative study has not been published yet. Thereforewe derive the frequency responses of the different prefilteredreconstruction techniques to analyze their global behavior suchas aliasing or smoothing. Furthermore, we introduce a novelmathematical basis to compare also their spatial-domain behaviorin terms of the asymptotic local error effect. For the sake of faircomparison, we use the same linear and cubic B-splines as basisfunctions but combined with different discrete prefilters. Ourgoal with this analysis is to help the potential users to select theoptimal prefiltering scheme for their specific applications.
Filtering, Sampling, Volume Visualization
Balázs Csébfalvi, "An Evaluation of Prefiltered Reconstruction Schemes for Volume Rendering", IEEE Transactions on Visualization & Computer Graphics, vol.14, no. 2, pp. 289-301, March/April 2008, doi:10.1109/TVCG.2007.70414
[1] M. Artner, T. Möller, I. Viola, and M.E. Gröller, “High-Quality Volume Rendering with Resampling in the Frequency Domain,” Proc. Joint EUROGRAPHICS-IEEE VGTC Symp. Visualization (EuroVis '05), pp. 85-92, 2005.
[2] T. Blu, P. Thévenaz, and M. Unser, “Generalized Interpolation: Higher Quality at No Additional Cost,” Proc. IEEE Int'l Conf. Image Processing, pp. 667-671, 1999.
[3] T. Blu, P. Thévenaz, and M. Unser, “Linear Interpolation Revitalized,” IEEE Trans. Image Processing, vol. 13, no. 5, pp. 710-719, 2004.
[4] I. Carlbom, “Optimal Filter Design for Volume Reconstruction and Visualization,” Proc. IEEE Visualization, pp. 54-61, 1993.
[5] Q. Chen, R. Crownover, and M. Weinhous, “Subunity Coordinate Translation with Fourier Transform to Achieve Efficient and Quality Three-Dimensional Medical Image Interpolation,” Medical Physics, vol. 26, no. 9, pp. 1776-1782, 1999.
[6] R. Cox and R. Tong, “Two- and Three-Dimensional Image Rotation Using the FFT,” IEEE Trans. Image Processing, vol. 8, no. 9, pp. 1297-1299, 1999.
[7] B. Csébfalvi, “Prefiltered Gaussian Reconstruction for High-Quality Rendering of Volumetric Data Sampled on a Body-Centered Cubic Grid,” Proc. IEEE Visualization, pp. 311-318, 2005.
[8] B. Csébfalvi and M. Hadwiger, “Prefiltered B-Spline Reconstruction for Hardware-Accelerated Rendering of Optimally Sampled Volumetric Data,” Proc. Vision, Modeling, and Visualization, pp.325-332, 2006.
[9] K. Hsu and T.L. Marzetta, “Velocity Filtering of Acoustic Well Logging Waveforms,” IEEE Trans. Acoustics, Speech and Signal Processing, vol. 37, no. 2, pp. 265-274, 1989.
[10] A. Li, K. Mueller, and T. Ernst, “Methods for Efficient, High Quality Volume Resampling in the Frequency Domain,” Proc. IEEE Visualization, pp. 3-10, 2004.
[11] S. Li and K. Mueller, “Accelerated, High-Quality Refraction Computations for Volume Graphics,” Proc. Volume Graphics, pp.73-81, 2005.
[12] S. Li and K. Mueller, “Spline-Based Gradient Filters for High-Quality Refraction Computations in Discrete Datasets,” Proc. Joint EUROGRAPHICS-IEEE VGTC Symp. Visualization (EuroVis '05), pp. 217-222, 2005.
[13] T. Malzbender, “Fourier Volume Rendering,” ACM Trans. Graphics, vol. 12, no. 3, pp. 233-250, 1993.
[14] S. Marschner and R. Lobb, “An Evaluation of Reconstruction Filters for Volume Rendering,” Proc. IEEE Visualization, pp. 100-107, 1994.
[15] D. Mitchell and A. Netravali, “Reconstruction Filters in Computer Graphics,” Proc. ACM SIGGRAPH '88, pp. 221-228, 1988.
[16] T. Möller, R. Machiraju, K. Mueller, and R. Yagel, “Classification and Local Error Estimation of Interpolation and Derivative Filters for Volume Rendering,” Proc. IEEE Symp. Volume Visualization, pp.71-78, 1996.
[17] T. Möller, R. Machiraju, K. Mueller, and R. Yagel, “Evaluation and Design of Filters Using a Taylor Series Expansion,” IEEE Trans. Visualization and Computer Graphics, vol. 3, no. 2, pp. 184-199, Apr.-June 1997.
[18] T. Möller, K. Mueller, Y. Kurzion, R. Machiraju, and R. Yagel, “Design of Accurate and Smooth Filters for Function and Derivative Reconstruction,” Proc. IEEE Symp. Volume Visualization, pp. 143-151, 1998.
[19] A.V. Oppenheim and R.W. Schafer, Discrete-Time Signal Processing, second ed. Prentice Hall, 1989.
[20] C. Sigg and M. Hadwiger, “Fast Third-Order Texture Filtering,” GPU Gems 2: Programming Techniques for High-Performance Graphics and General-Purpose Computation, M. Pharr, ed., Addison-Wesley, pp. 313-329, 2005.
[21] G. Strang and G. Fix, “A Fourier Analysis of the Finite Element Variational Method,” Constructive Aspects of Functional Analysis, pp. 796-830, 1971.
[22] T. Theußl, H. Hauser, and M.E. Gröller, “Mastering Windows: Improving Reconstruction,” Proc. IEEE Symp. Volume Visualization, pp. 101-108, 2000.
[23] P. Thévenaz, T. Blu, and M. Unser, “Interpolation Revisited,” IEEE Trans. Medical Imaging, vol. 19, no. 7, pp. 739-758, 2000.
[24] R. Tong and R. Cox, “Rotation of NMR Images Using the 2D Chirp-z Transform,” Magnetic Resonance in Medicine, vol. 41, no. 2, pp. 253-256, 1999.
[25] M. Unser, P. Thévenaz, and L. Yaroslavsky, “Convolution-Based Interpolation for Fast, High-Quality Rotation of Images,” IEEE Trans. Image Processing, vol. 4, no. 10, pp. 1371-1381, 1995.
[26] M.A. Westenberg and J.B.T.M. Roerdink, “Frequency Domain Volume Rendering by the Wavelet X-Ray Transform,” IEEE Trans. Image Processing, vol. 9, no. 7, pp. 1249-1261, 2000.
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