2008/8/6 Matthieu Brucher <[EMAIL PROTECTED]>: > Exactly. Using FFT to do a convolution should be done after some > signal processing readings ;)
When you convolve two signals, of lengths N and M, you need to pad the FFTs to length (N+M-1) before multiplication. You can take a look at my linear position-invariant filtering code at: http://mentat.za.net/hg/filter To construct a Gaussian filter, for example, you do: >>> def filt_func(r,c): return np.exp(-np.hypot(r,c)/1) >>> filter = LPIFilter2D(filt_func) You may then apply it on data by doing `filter(data)`. I also implemented inverse filtering, which can be accessed using `filter.inverse` and `filter.wiener`. Regards Stéfan _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
