ABSTRACT
The chi-squared difference has advantages over the most other measures that have been used to quantify the difference between experimental and simulated images. In particular, if reliable estimates of the noise statistics are available it can directly quantify the plausibility of an experimental image given a particular specimen and imaging model. Applied in Fourier space, it is the only measure that remains interpretable when the image noise is not normally distributed or when - as is normally the case - the noise in neighbouring image pixels is not independent.
