Noise filtering
X-ray medical imaging. 2D image processing

Let's focus on the case of an image whose noise is of quantum origin (electronic noise is neglected, which is legitimate most of the time): if N represents the signal per pixel (in number of primary quanta absorbed), the average signal, then √ represents the noise level and (consequently) the signal-to-noise ratio. The Anscombe transform involves substituting its square root (N → 2√(N + 3/8)) for the signal. Francis Anscombe showed in 1948