CImCombine:SetNormStat

The SetNormStat method specifies the statistic used to determine the correction needed to normalize each image to the reference image. The statistics are similar to those used by the combining methods, except that the normalization statistic produces a single number applied to the entire image.

Syntax

CImCombine:SetNormStat( stat, par1, par2, par3 )

stat specifies the statistic (see table in the Remarks section, below).

par1, par2, and par3 are optional parameters used by the various statistics.

Remarks

The normalization statistic may be any of the methods listed in the table below. Parameters are also listed. If not specified, as an argument, all parameters adopt reasonable values. For example, the default values for sigma clipping parameters are 2.5, the default values for alpha clipping parameters are 1, and the default values for rank clipping parameters are 2.5 (percentile). Both power parameters default to 0.5.

Normalization Methods

Stat Name	Description of the Statistic	Par1	Par2	Par3
Alpha Clip	Mean, excluding alpha high values and alpha low values. See AlphaClip	nHigh	nLow
Contra Mean	The contra-harmonic mean of pixel values. See ContraMean	power
Geometric Mean	The geometric mean of pixel values. See GeometricMean
Max	Maximum pixel value
MaxClip	Mean, excluding maximum pixel value. See MaxClip
Mean	Unweighted mean value
Median	Median value
Min	Minimum pixel value
MmClip	Mean, excluding maximum and minimum pixel values. See MmClip
Mtm Sigma Clip	Mean, excluding values outside upper and lower sigma limits relative to the median. See MtmSigmaClip	nHigh	nLow	nIter
Rank	Rank percentile value. See Rank	percentile
Rank Clip	Mean after clipping pixel values above and below rank percentiles. See RankClip	pHigh	pLow
Sigma Clip	Mean, excluding values outside upper and lower sigma limits. See SigmaClip	nHigh	nLow	nIter
Yp Mean	The Yp Power weighted mean of pixel values. See YpMean	power

Example

The following script uses SetNormStat to specify the normalization statistic as sigma clipping with 2.5 sigma rejection above and 5 sigma rejection below the mean:

C = new_imcombine()	-- create a CImCombine object
R = new_rect(10,50,10,50)	-- central 10% of the image
C:SetRelRect( R )	-- specify CImage and CRect to measure
C:SetNormStat("sigma clip",2.5,5)	-- use the median as the statistic
C:SetNormStat("scale")	-- scale to normalize the image set
I = C:Mean( S )	-- combine image set and return new image
I:Display()	-- show the new image
C:delete()	-- when done with S, remove it from memory

Syntax

Remarks

Example

Related Topics