A method for estimating noise variance of CT image

Rank et al. have proposed an algorithm for estimating image noise variance composed of the following three steps: the noisy image is first filtered by a difference operator; a histogram of local signal variances is then computed; and, finally the noise variance is estimated from a statistical evaluation of the histogram. We have verified the accuracy of this algorithm on a CT image by indirect methods, and have shown that this method is able to estimate CT image noise variance with reasonable accuracy, regardless of whether or not the noiseless image is uniform. Further, we have proposed a simple alternative method for the last two steps of the Rank et al. method. However, one must pay attention to the fact that the estimated noise variance will be biased when the nearest two pixels are correlated and that this algorithm does not work well if the assumption of stationarity of noise components is violated.