[PD] signal weighted median filtering
czhenry at gmail.com
Sun Jul 22 04:41:11 CEST 2007
Originally, I was writing an external for this, and it turned out to
be very buggy. I will get back to work on it, after while, once some
other projects get finished :)
The main comparison with lop~ or other linear filters is that the
impulses disturb the mean of the signal. The median is much more
resistant to outliers than mean, so it works better for representing
the most likely accurate sample out of a collection of samples. It's
probably best for filtering measurements.
I'm still not so sure on how the weighting should work, but it should
also have some spectral effects, like low-pass filtering for the right
choice of weights.
On 7/21/07, Hans-Christoph Steiner <hans at eds.org> wrote:
> Just going thru old list emails that I missed. This is interesting,
> it seems to work pretty well. It would be nice to see it compared to
> other techniques and using other input signals. I quickly added a
> lop~ for comparison:
> On May 26, 2007, at 2:02 AM, Andy Farnell wrote:
> > Nice. The graph says it all, it really snuffs out those spikes.
> > Yeah, and it eats way too much CPU, but I enjoy the instructional
> > value of seeing this filter done as signal expressions.
> > Andy
> > On Fri, 25 May 2007 14:01:21 -0500
> > "Charles Henry" <czhenry at gmail.com> wrote:
> >> Hi, list,
> >> I've created an abstraction for performing weighted median
> >> filtering
> >> on a signal using 5 coefficients. It's a real cpu hog. It uses
> >> heavily the expr, expr~ and fexpr~ externals, which leads to some
> >> redundant calculations on each sample.
> >> The test patch enclosed shows how effective this can be for
> >> removing
> >> impulsive noises from a signal (like the pops on a record).
> >> Chuck
> > --
> > Use the source
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