The Image Combiner program has six different methods of stacking luminance images. Identical methods for color frames are provided by the LRGB Color program. The Image Combiner also processes batches of images for dark frame subtraction, flat-fielding, debayering and pixel squaring. ADD OR AVERAGE: The two fastest stacking methods are to simply sum or average the images, and both of these methods produce the maximum amount of statistical noise reduction. Neither method, however, provides any immunity from cosmic ray strikes or meteor tracks. (The summed stack is often useful in keeping track of the total acquired intensity of an imaging session for cases where the results of several sessions are to be combined.) MEDIAN AVERAGE: The median average, unlike the simple average, provides nearly complete immunity from the effects of cosmic rays or meteor tracks. On the other hand its noise reduction is less than either the sum or average unless the number of combined images is quite large. SIGMA-KAPPA: The Sigma-Kappa average is designed to provide the best features of the numerical average and the median average. This method calculates the standard deviation of the intensities (sigma) for each pixel, and rejects the value if it differs from the mean by more than kappa times sigma. By selecting a kappa value of 6 or more it is usually possible to eliminate the effects of cosmic rays and meteors while achieving nearly the same amount of noise reduction as a direct average. Choosing smaller kappa values eventually begins to smooth the image and reject too much of the signal. ARTIFICIAL SKEPTICISM: An alternative approach is to not reject any values in calculating the average, but to simply weight their contribution less if they are farther from the mean. This is the method of artificial skepticism which uses a Lorentzian weighting function. Artificial skepticism is useful for combining images obtained in changing observing conditions or on different days. Artificial skepticism suppresses the effects of cosmic rays and meteors but may not completely eliminate them. ENTROPY AVERAGE: Entropy stacking is the most computationally intensive method. It also weights the contribution of each pixel, not by a statistical value, but by the entropy of the pixels surrounding the pixel in each image. Thus pixels in images with high contrast contribute fully, while pixels on images dimmed by cloud cover contribute little. Entropy stacking is also useful in rejecting contributions from empty regions created by registering images. While entropy stacking does nothing to eliminate cosmic rays and meteor tracks, it is possible to eliminate them manually by using the meteor or dodge tools of the image aligner program. © Laser Diagnostics 2006-2009 IMAGE  STACKING