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List:       schrodinger-devel
Subject:    Re: [Schrodinger-devel] Filters / wavelets / median filtering / denoising
From:       yann.lepetitcorps () free ! fr
Date:       2012-05-19 11:58:06
Message-ID: 1337428686.4fb78ace7599f () imp ! free ! fr
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> > > > This is only used in the center-weighted median code, which must
> > > > be specifically enabled.  CWM is particularly bad at filtering out
> > > > noise in video, especially the kind of noise that make video encoders
> > > > less efficient.
> > 
> > > > Sorting neighboring pixel values is a particularly dumb method of
> > > > doing a CWM filter (when all you want is the median), so fixing the
> > > > dumb method of sorting is not really going to make the code good.
> > > > The correct way to do CWM is roughly min(max(center,min(neighbors),
> > > > max(neighbors)), at least for weight=4.  (IIRC, this is from memory)
> > 
> > ...
> > 
> > > I take a look about how to make median filtering / denoising into a SIMD
> > way
> > > and
> > > come back when I have find enough interesting infos on the subject
> > > 
> > 
> > I have take a look at
> > 
> 
[url]http://www.google.fr/url?sa=t&rct=j&q=center+weighted+median+&source=web&cd=4&ved \
=0CG0QFjAD&url=http%3A%2F%2Fwww.cs.tut.fi%2F~moncef%2Fpublications%2Fanalysis-of-two-m \
ssp95.pdf&ei=o0W3T6-yD-rK0QXmyqDlBw&usg=AFQjCNGUSN9BSC2IyjVY7yQjPxPx31dpyA&cad=rja[/url]

> > 
> > This can certainly to be handled by the use of de Haar wavelets or
> something
> > like this, no ?
> > (I discovered the Harr/Debauchies wavelets only the last year, but this
> > really
> > seem good suited for to can manage larges images that are "smoothed" while
> > being
> > able to have numerous detailled areas inside ... or to handle denoising of
> > course :) )
> > 
> > I think too that the numerous OpenGL texturing facilities can certainly to
> be
> > precious compagnons for to explore the SIMD way ...
> 
> I think to begin with a "basic" 3 by 3 window bidirectional MMF and hope to
> begin to address the Multilevel structure which is equivalent to CWM(9,5)
> with 3
> by 3 square window before the end of the year :)

I have understand why you want very fastly reordering values from a very little
and unordered list of value :)

Property 2.1. The output y(i,j) of a CWM filter with window size M and center
weight 2 K + 1 can be represented by

y(i, j) = med{x(((M + 1)/2) - K; M), x(i, j), x(((M + 1)/2) + K; M)},

where x(r; M) denotes the rth smallest sample among the M samples within the
window
centered at (i, j), and x(i, j) is the input value at the center of the window.

=> I begin to search the best method for to find the n firsts values in a small
a unordered list of 9 samples/values


@+
Yannoo

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