For best results, images contained in an image stack should have the same dimensions and mostly similar content, such as a set of still images taken from a fixed viewpoint, or a series of frames from a stationary video camera. The content of your images should be similar enough to allow you to register or align them to other images in the set.
Stack modes operate on a per-channel basis only, and only on non-transparent pixels. For example, the Maximum mode returns the maximum red, green, and blue channel values for a pixel cross-section and merges those into one composite pixel value in the rendered image.
Rendering plug‑in name |
Result |
Comments |
---|---|---|
Entropy |
entropy = - sum( (probability of value) * log2( probability of value) ) Probability of value = (number of occurrences of value) / (total number of non-transparent pixels) |
The binary entropy (or zero order entropy) defines a lower bound on how many bits would be necessary to losslessly encode the information in a set. |
Kurtosis |
kurtosis = ( sum( (value - mean)4 ) over non-transparent pixels ) / ( ( number of non-transparent pixels - 1 ) * (standard deviation)4 ). |
A measure of peakedness or flatness compared to a normal distribution. The kurtosis for a standard normal distribution is 3.0. Kurtosis greater than 3 indicates a peaked distribution, and kurtosis less than 3 indicates a flat distribution (compared to a normal distribution). |
Maximum |
The maximum channel values for all non-transparent pixels |
|
Mean |
The mean channel values for all non-transparent pixels |
Effective for noise reduction |
Median |
The median channel values for all non-transparent pixels |
Effective for noise reduction and removal of unwanted content from the image |
Minimum |
The minimum channel values for all non-transparent pixels |
|
Range |
Maximum minus the minimum of the non-transparent pixel values |
|
Skewness |
skewness = (sum( (value - mean)3 ) over non-transparent pixels ) / ( ( number of non-transparent pixels - 1 ) * (standard deviation)3 ) |
Skewness is a measure of symmetry or asymmetry around the statistical mean |
Standard Deviation |
standard deviation = Square Root(variance) |
|
Summation |
The sum channel values for all non-transparent pixels |
|
Variance |
variance = (sum( (value-mean)2 ) over non-transparent pixels ) / ( number of non-transparent pixels - 1) |
Because an image stack is a Smart Object, you can edit the original images that make up the stack layers at any time.