CStats:MtmSigmaClipMean

CStats:MtmSigmaClipMean and CStats:MtmSigmaClipMeanSdev

The MtmSigmaClipMean method computes the mean value inside a rectangular region of the image, using the modified trimmed mean method for removing deviant values from the statistic. The clipping is described by 3 parameters nHigh, nLow, and nIter. These specify the number of sigmas above, number of sigmas below, and number of iterations, respectively. Typical values are 3, 3, 3.

Syntax

nMean = CStats:MtmSigmaClipMean( CImage, nHigh, nLow, nIter, CRect )

nMean = CStats:MtmSigmaClipMean( CImage, nHigh, nLow, nIter )

nMean = CStats:MtmSigmaClipMean( table, nHigh, nLow, nIter )

nMean, nSdev = CStats:MtmSigmaClipMeanSdev( CImage, nHigh, nLow, nIter, CRect )

nMean, nSdev = CStats:MtmSigmaClipMeanSdev( CImage, nHigh, nLow, nIter )

nMean, nSdev = CStats:MtmSigmaClipMeanSdev( table, nHigh, nLow, nIter )

CImage is an image object.

table is a 1-dimensional array containing numbers.

CRect is a bounding rectangle for the CImage object.

nHigh is the number of sigmas at which to clip above the distribution.

nLow is the number of sigmas at which to clip below the distribution.

nIter is the number of iterations of clipping, usually 3 to 5.

On success, this method returns the MTM clipped mean value as a number.

On failure, returns 0.

Remarks

The MTM Mean is a "Modified Trimmed Mean" which removes deviant values relative to the Median, rather than the Mean of the sample distribution. The returned value is the mean of the final sample of non-rejected points. This algorithm trims bad data away from the mean value using the standard deviation and median value in an iterative fashion. Use this method to reduce the biased result when the region contains a large percentage of deviant pixel values. This method uses the same algorithm as MtmSigmaClip in the CImCombine class.

Example

Suppose a CImage I and a CRect R exist. The following script returns the MTM clipped mean value inside a rectangle on the image. The clipping is done at 3 sigmas above the mean and 5 sigmas below the mean:

S = new_stats()	-- create a CStats object
-- specify CImage and CRect to measure
nMean = S:MtmSigmaClipMean( I,3,5,2,R )	-- clip 3 sigmas above, 5 sigmas below, 2 iterations
Printf("mean=%lg\n", nMean )	-- list the results
S:delete()	-- when done with S, remove it from memory

Syntax

Remarks

Example

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