Image quality assessment based on a degradation model

We model a degraded image as an original image that has been subject to lin ear frequency distortion and additive noise injection. Since the psychovisu al effects of frequency distortion and noise injection are independent, we decouple these two sources of degradation and measure their effect on the h uman visual system. We develop a distortion measure (DM) of the effect of f requency distortion, and a noise quality measure (NQM) of the effect of add itive noise. The NQM, which is based on Peli's contrast pyramid, takes into account the following: 1) variation in contrast sensitivity with distance, image dimensions, and s patial frequency; 2) variation in the local luminance mean; 3) contrast interaction between spatial frequencies; 4) contrast masking effects. For additive noise, we demonstrate that the nonlinear NQM is a better measu re of visual quality than peak signal-to-noise ratio (PSNR) and linear qual ity measures. We compute the DM in three steps. First, we find the frequenc y distortion in the degraded image. Second, we compute the deviation of thi s frequency distortion from an allpass response of unity gain (no distortio n). Finally, we weight the deviation by a model of the frequency response o f the human visual system and integrate over the visible frequencies. me de monstrate how to decouple distortion and additive noise degradation in a pr actical image restoration system.