The Wavelet tool performs de-noising of dynamic data, whereby the x and y image dimensions must be a power of 2. Note that if the z and the time domain sizes are not a power of 2, they are extended or reduced to the closest 2n value.
Wavelet filtering has been adapted from [1] and can be applied with two sets of coefficients:
•Daubechies using 20 coefficients [1];
•Battle-Lemarie using 71 coefficients obtained from Narayan Kovvali, at that time working at Duke University.
There are four different filtering modes:
•each plane separately (2D),
•each frame separately (3D),
•each plane over time separately (2D + time),
•or the entire volume over time (3D + time).
The coefficients to keep determine the level of smoothing: the lower the % value entered, the smoother the image.
Reference
1.William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery. 1992. Numerical Recipes in C (2nd Ed.): The Art of Scientific Computing. Cambridge University Press, New York, NY, USA.