A new model of perceptual threshold functions for application in image compression systems

Abstract

This paper discusses the development of a perceptual threshold model for the human visual system. The perceptual threshold functions describe the levels of distortions present at each location in an image that human observers can not detect. Models of perceptual threshold functions are useful in image compression problems because an image compression system that constrains the distortion in the coded images below the levels suggested by the perceptual threshold function performs perceptually lossless compression. Our model involves the decomposition of an input image into its Fourrier components and spatially localized Gabor elementary functions. Data from psychophysical masking experiments are then used to calculate the perceptual detection threshold for each Gabor transform coefficient in the presence of sinusoidal masks. The result of one experiment involving distorting an image using additive noise of magnitudes as suggested by the threshold model is also included in this paper.