| Re: efficient kernel or masking algorithm ? UPDATE [message #85304 is a reply to message #23913] |
Tue, 23 July 2013 13:35  |
PMan
Messages: 61
Registered: January 2011
|
Member |
|
|
On Monday, February 26, 2001 10:38:06 AM UTC-5, Martin Downing wrote:
> "John-David Smith" <jdsmith@astro.cornell.edu> wrote in message
> news:3A99C6B4.10549265@astro.cornell.edu...
>>
>> P.S. I think I originally got the idea from sigma_filter.pro, a NASA
> library
>> routine, dating back to 1991. It's chock-full of other good tidbits too.
>> Thanks Frank and Wayne!
>
> Hi John,
> Just checked the file SIGMA_FILTER.pro at
> http://idlastro.gsfc.nasa.gov/ftp/pro/image/?N=D
> I really must spend more time browsing these great sites.
> The code is similar, however it does not calculate the true variance under
> the mask
> they calculate for a box width of n, (ignoring centre pixel removal):
> --------------------------------------
> mean_im=(smooth(image, n) )
> dev_im = (image - mean_im)^2
> var_im = smooth(dev_im, n)/(n-1)
> -------------------------------------
> This is not the true variance of the pixels under the box mask, as each
> pixel in the mask is having a different mean subtracted.
> i.e (read this as a formula if you can!)
> Pseudo_Variance = SUM ij ( ( I(x+i,y+j) - MEAN(x+i,y+j)^2) /(n-1)
>
> instead of true variance:
> Variance = SUM ij ( ( I(x+i,y+j) - MEANxy)^2) /(n-1)
> which can be reduced to : {(SUM ij ( ( I(x+i,y+j)^2 ) - (SUM ij
> I(x+i,y+j) ) ^2)/n }/(n-1)
> hence the non loop method we use below:
> ---------------------------
> ; calc box mean
> mean_im = smooth(image, n)
> ; calc box mean of squares
> msq_im = smooth(image^2, n)
> ; hence variance
> var_im = ( msq_im - mean_im^2) * (n/(n-1.0))
> ----------------------------------
>
> cheers
>
> Martin
>
> PS: Sorry about my before-and-after-coffee postings this morning, outlook
> decided to post my replies whilst I was still pondering - how kind - I've
> killed that *feature* now :)
n seems to mean two things in your code: in the smooth function it is the window width and in your final variance calculation line it means number of samples. These should not be the same. If n is window size then the final line should read:
; hence variance
var_im = ( msq_im - mean_im^2) * (n*n/((n*n)-1.0))
Right? Or did I misunderstand something?
|
|
|
|
comp.lang.idl-pvwave archive
Members
Search
Help
Login
Home
