Antivibration Stereo Image by Curvelet
Main Article Content
Abstract
In this paper, we present image of noise reduction and vibration problems by curvelet method. For particular stereo image and 1D, 2D, 3D, MD (multidimensional signals in general, the mutation points contain important information and must be preserved). By using curvelet transform can make use of the advantages and limit disadvantages of the method. Secondly, enhancing the sustainability base on curvelet transformation and enhance the effectiveness of vibration and noise elimination. The effectiveness of the method when using PSF and evaluation of PSF to the value of arrays of RMSE values and PSNR to reconstruct effective image from vibrating image.
Keywords
Antivibration, Curvelet transformation, Stereo image processing, Image Denoising
Article Details
References
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2. Sendur, L., Selesnick, I. W. - Bivariate shrinkage functions for Wavelet-based denoising exploiting interscale dependency, IEEE on Trans. Signal Processing., 50(2002):2744-2756.
3. François G. Meyer - Wavelet-Based Estimation of a Semiparametric Generalized Linear Model of FMRI Time-Series, IEEE Trans. on Medical Imaging 22(2003):3.
4. Christopher B. Smith, Sos Agajan, and David Akopian - A Wavelet-Denoising Approach Using Polynomial Threshold Operators, IEEE Trans. Signal Processing Lets., 15(2008).
5. E.Candues, L. Demanet, D.Donoho, L. Ying, Fast discrete curvelettransforms, Multiscale Model. Simul., 5(2006)3:861-899.
6. E.Candues, D. Donoho, Continuous curvelet transform: I. Resolution of the wavefront set, Appl. Comput. Harmon. Anal., 19(2003)162-197.