Image noise severity metric

We propose in this paper an image noise severity measurement method that correlates well with human's quality perception on the presence of noise in images. In our approach, a 32x32 pixels mask is used to compute the differences between the original and noise-degraded images in terms of the statistical means and outlier values. These differences are formulated and then compared to the quality scores from the subjective evaluations. The degraded images were distorted by two common types of random noise for images - Gaussian white noise and impulse noise. Experiment results showed that this approach obtained higher correlation compare to classical Peak Signal to Noise Ratio (PSNR) method