Image Region Statistics
Mira provides several methods for computing a statistical estimator inside a rectangular region of an image. These estimators are usually measured using the Region Statistics dialog.
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 Region Statistics Estimators  | 
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 Mean  | 
 Calculates the arithmetic mean value of all pixels inside the reference region with no rejection of extreme values. This is the preferred method if the region contains only well-behaved statistical noise.  | 
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 Mean - Alpha Clipped  | 
 This is a general case of the Min/Max clipping method. Here, you specify the number of high values to clip and the number of low values to clip. In comparison, the Min/Max method rejects only the 1 highest and 1 lowest values.  | 
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 Mean - Sigma Clipped  | 
 Computes the arithmetic mean after iteratively rejecting extreme values more than sigma's from the mean value. The rejection is 2-tailed, and the upper and lower sigma multipliers are specified independently. For example, setting High Sigma = 2.5 and Low Sigma = 5.0, then the statistic is computed using values within 2.5 sigma's above the mean and 5.0 sigma's below the mean.  | 
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 Median  | 
 Creates an image containing the Median values of all images at each point. This method has good ability to reject extreme values. For a given number of input images, the noise in the resulting image is not as low as that which can result from Mean combining methods.  | 
Region Statistics, Image Combining Methods, Combine Image Set, Normalize Image