Selon David Schleef <d...@schleef.org> :
> > 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)
If this is only for to find the median, this code seem to produce a good
approximation of the true median for a 3x3 patch (in fact, this seem to return
the true median value the majority of time)
inline int median3(int a, int b, int c)
{
if ( a <= b )
{
if ( b <= c )
return b;
if ( c <= a )
return a;
return c;
}
// a > b
if ( a <= c )
return a;
if ( b <= c )
return c;
return b;
}
void fast_median3x3(int *d)
{
int m1, m2 ,m3, m4;
m1 = median3(d[0], d[1], d[2]);
m2 = median3(d[3], d[4], d[5]);
m3 = median3(d[6], d[7], d[8]);
return median3(m1,m2,m3);
}
Note that the median3() func is coded very ugly and can certainly to be coded
for to be very more speed
(it only return the median from 3 values)
On other side, I have found something that produce one approximation of
the median for patchs biggers than 3x3, but the value returned can be very far
from the true median value :(
(n=9 for 3x3 patchs and n have always to be >= 3)
int approx_median(int *d , int n)
{
int i, v, imin=255, imax=-255, sum = 0;
for (i= 0; i < n; i++ )
{
v = d[i];
if (v < imin )
{
imin = v;
}
else
if ( v > imax )
{
imax = v;
}
sum += v;
}
return (sum - imin - imax)/(n-2);
}
In fact, this compute the mean but without the minimum and maximum extrems
values
(this can for example to be used for to filter pictures with a little impulsed
white noise)
PS : I always don't understand the signification of
"min(max(center,min(neighbors),max(neighbors)), at least for weight=4" :(
@+
Yannoo
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