P^2SNR: Perceptual Full-Reference Image Quality Assessment for JPEG2000

摘要

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 visual 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.