Estimation of image quality is decisive in the image compression field. This is important in order minimize, induced error via rate allocation. Traditional full-reference algorithms of image quality try to model how Human Visual System detects visua differences and extracts both information and structure of the image. In this work we I propose a quality assessment, which weights the mainstream PSNR by means of a perceptual model (P2SNR). Perceptual image quality is obtained by estimating the rate of energy loss when an image is observed at monotonically increasing distances.