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Issue No.02 - March/April (2009 vol.11)
pp: 72-80
Jianwei Ma , Tsinghua University
Gerlind Plonka , University of Duisburg-Essen
The curvelet transform allows an almost optimal nonadaptive sparse representation for curve-like features and edges. The authors describe some recent applications involving image processing, seismic data exploration, turbulent flows, and compressed sensing.
Computer simulations, computational science, engineering, curvelets, turbulent flow
Jianwei Ma, Gerlind Plonka, "Computing with Curvelets: From Image Processing to Turbulent Flows", Computing in Science & Engineering, vol.11, no. 2, pp. 72-80, March/April 2009, doi:10.1109/MCSE.2009.26
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20. G. Plonka and J. Ma, "Nonlinear Regularized Reaction-Diffusion Filters for Denoising of Images with Textures," IEEE Trans. Image Processing, vol. 17, no. 8, 2008, pp. 1283–1294.
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28. J. Ma and M. Hussaini, "Three-Dimensional Curvelets for Coherent Vortex Analysis of Turbulence," Applied Physics Letters, vol. 91, no. 18, 2007, pp. 184101:1–3.
29. E. Candes, J. Romberg, and T. Tao, "Stable Signal Recovery from Incomplete and Inaccurate Measurements," Comm. Pure Applied Mathematics, vol. 59, no. 8, 2005, pp. 1207–1233.
30. E. Candes and T. Tao, "Decoding by Linear Programming," IEEE Trans. Information Theory, vol. 51, no. 12, 2005, pp. 4203–4215.
31. D. Donoho, "Compressed Sensing," IEEE Trans. Information Theory, vol. 52, no. 4, 2006, pp. 1289–1306.
32. J. Ma and F.-X. Le Dimet, "Deblurring from Highly Incomplete Measurements for Remote Sensing," to be published in IEEE Trans. Geoscience Remote Sensing, 2008.
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