Noise Removal Using HWD Implemented by Dmeyer and Kaiser Window

Author:

Ghanbarisabagh MohammadORCID,Vetharatnam Gobi,Babak Setareh

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Reference14 articles.

1. Mallat, S. (1998). A wavelet tour of signal processing (2nd ed.). New York: Academic.

2. Vetterli, M. (2001). Wavelets, approximation and compression. IEEE Signal Processing Magazine, 18(5), 59–73.

3. Candes, E. J., & Donoho, D. L. (1999). Curvelets—A surprisingly effective nonadaptive representation for objects with edges. In A. Cohen, C. Rabut, & L. L. Schumaker (Eds.), Curve and surface fitting. Nashville, TN: Vanderbuilt Univ. Press.

4. Portilla, J., Strela, V., Wainwright, M. J., & Simoncelli, E. P. (2003). Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Transactions on Image Processing, 12(11), 1338–1351.

5. Sendur, L., & Selesnick, I. W. (2002). Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency. IEEE Transactions on Signal Processing, 50(11), 2744–2756.

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