Analysis of effect of cycle spinning on wavelet- and curvelet-based denoising methods on brain CT images

References

• Candes, E. J., L. Demanet, D. L. Donoho, and L. Ying. 2005. “Fast Discrete Curvelet Transforms [Online].” Stanford University. Accessed November 10 2010. http://www.curvelet.org.papers.FDCT.pdf.
   Google Scholar
• Chang, B., and M. Vetterli. 2000. “Adaptive Wavelet Thresholding for Image Denoising and Compression.” IEEE Transactions on Image Processing 9 (9): 1532–1546.10.1109/83.862633
   PubMed Web of Science ®Google Scholar
• Coifman, R. R., and D. L. Donoho. 1995. “Translation Invariant De-noising.” In Wavelets and Statistics, Lecture Notes in Statistics 103, 125–150. New York: Springer-Verlag.
   Google Scholar
• Deans, S. R. 1983. The Radon Transform and Some of Its Application. New York: Wiley.
   Google Scholar
• Donoho, D. L. 1995. “De-noising by Soft-thresholding.” IEEE Transactions on Information Theory 41 (3): 613–627.10.1109/18.382009
   Web of Science ®Google Scholar
• Donoho, D. L., M. R. Duncan. 1999. “Digital Curvelet Transform: Strategy, Implementation and Experiments [Online].” Stanford University. Accessed November 5 2010. http://www-stat.stanford.edu/~donoho/Reports/1999/DCvT.pdf.
   Google Scholar
• Donoho, D. L., and I. M. Johnstone. 1995. “Adapting to Unknown Smoothness via Wavelet Shrinkage.” Journal of the American Statistical Association 90 (432): 1200–1224.10.1080/01621459.1995.10476626
   Web of Science ®Google Scholar
• Garvey, J., and R. Hanlon. 2002. “Computed Tomography in Clinical Practice.” British Medical Journal 324 (7345): 1077–1080.10.1136/bmj.324.7345.1077
   PubMed Web of Science ®Google Scholar
• Gravel, P., G. Beaudoin, and J. A. De Guise. 2004. “A Method for Modeling Noise in Medical Images.” IEEE Transactions on Medical Imaging 23 (10): 1221–1232.10.1109/TMI.2004.832656
   PubMed Web of Science ®Google Scholar
• Ismail, I. A., and T. Nabil. 2004. “Applying Wavelet Recursive Translation-invariant to Window Low-pass Filtered Images.” International Journal of Wavelets, Multiresolution and Information Processing 2 (1): 99–110.10.1142/S0219691304000378
   Google Scholar
• Lee, J. S. 1980. “Digital Image Enhancement and Noise Filtering by Use of Local Statistics.” IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-2 (2): 165–16810.1109/TPAMI.1980.4766994
   Web of Science ®Google Scholar
• Lee, J. S. 1981. “Refined Filtering of Image Noise Using Local Statistics.” Computer Graphics and Image Processing 15 (4): 380–389.10.1016/S0146-664X(81)80018-4
   Google Scholar
• Lu, H., I. Hsiao, X. Li, and Z. Liang. 2001. “Noise Properties of Low-dose CT Projections and Noise Treatment by Scale Transformations.” In IEEE Nuclear Science Symposium Conference Record, San Diago, CA, 4–10 November 2011: 1662–1666. New York: IEEE.
   Google Scholar
• Oliver, C., and S. Quegan. 1999. Understanding Synthetic Aperture Radar Images. Boston, MA: Artech House.
   Google Scholar
• Qin, S., C. Yang, B. Tang, and S. Tan. 2002. “The Denoise Based on Translation Invariance Wavelet Transform and Its Applications.” In A Conference on Structural Dynamics, Los Angeles, CA, 4–8 February 2002: 783–787.
   Google Scholar
• Starck, J. L., E. J. Candes, and D. L. Donoho. 2002. “The Curvelet Transform for Image Denoising.” IEEE Transactions on Image Processing 11 (6): 670–684.10.1109/TIP.2002.1014998
   PubMed Web of Science ®Google Scholar
• Starck, J. L., F. Murtagh, E. J. Candes, and D. L. Donoho. 2003. “Gray and Color Image Contrast Enhancement by the Curvelet Transform.” IEEE Transactions on Image Processing 12 (6): 706–717.10.1109/TIP.2003.813140
   PubMed Web of Science ®Google Scholar
• Wang, A. C., and A. Bovik. 2002. “A Universal Image Quality Index.” IEEE Signal Processing Letters 9 (3): 81–84.10.1109/97.995823
   Web of Science ®Google Scholar
• Wang, A., Z. Ye, S. Meng, and M. Yang. 2008. “Image Denoising Method Based on Curvelet Transform.” In 3rd IEEE Conference on Industrial Electronics and Applications, Singapore, 3–5 June 2008: 571–574. New York: IEEE.
   Google Scholar
• Wang, Z., A. Bovik, H. Sheikh, and E. Simoncelli. 2004. “Image Quality Assessment: From Error Visibility to Structural Similarity.” IEEE Transactions on Image Processing 13 (4): 600–612.10.1109/TIP.2003.819861
   PubMed Web of Science ®Google Scholar