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.

Region Statistics Estimators

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.

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.

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.

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.

Related Topics

Region Statistics, Image Combining Methods, Combine Image Set, Normalize Image