Noise removal approach using Curvelet transform

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[2] Emmanuel J. CANDèS,David L. DONOHO. Continuous Curvelet Transform:Resolution of the Wavefront Set[EB/OL]. Available:www-stat.stanford.edu/～donoho/Reports/2003/ContCurveletTransform-I.pdf,2003-5-6/2004-8-15.

[3] Emmanuel J. CANDèS,David L. DONOHO. Continuous Curvelet Transform:Discretization and Frames [EB/OL]. Available:www-stat.stanford.edu/～donoho/Reports/2003/ContCurveletTransform-II.pdf,2003-5-6/2004-8-15.

[4] Emmanuel J. CANDèS,David L. DONOHO. Curvelets-a surprisingly effective nonadaptive representation for objects with edges [EB/OL]. http://www.acm.caltech.edu/～emmanuel/papers/Curvelet-SMStyle.pdf,1999-12-16/2004-9-20.

[5] Jean-Luc STARCK,Emmanuel J. CANDèS,David L. DONOHO. The Curvelet transform for image denoising[J]. IEEE Trans Image Proc,2002,11(6):670-684.

[6] Jean-Luc STARCK,Fionn MURTAGH,Emmanuel J. CANDèS,et al. Gray and Color Image Contrast Enhancement by the Curvelet Transform[J]. IEEE Trans Image Proc,2003,12(6):706-716.

[8] David L. DONOHO,Mark R. DUNCAN. Digital Curvelet transform:strategy,implementation and experiments[J]. SPIE, 2000,4056:12-29.

[9] Tony T. CAI,Bernard W. SILVERMAN. Incorporating information on Neighbouring Coefficients into wavelet estimation[J]. The Indian Journal of Statistics,2001,63(2B):127-148.

[10] PAN Quan,ZHANG Lei,ZHANG Hongcai,et al. Adaptive wavelet based spatially denoising [J]. IEEE Trans. Signal Processing,1998,18(2):486-489.

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