Image quality assessment with a Gabor pyramid model of the human visual system

Reliable image quality assessments are necessary for evaluating digital imaging methods (halftoning techniques) and products (printers, displays). Typically the quality of the imaging method or product is evaluated by comparing the fidelity of an image before and after processing by the imaging method or product. It is well established that simple approaches like mean squared error do not provide meaningful measures of image fidelity. A number of image fidelity metrics have been developed whose goal was to predict the amount of differences that would be visible to a human observer. In this paper we outline a new model of the human visual system (HVS) and show how this model can be used in image quality assessment. Our model departs from previous approaches in three ways: (1) We use a physiologically and psychophysically plausible Gabor pyramid to model a receptive field decomposition; (2) We use psychophysical experiments that directly assess the percept we wish to model; and (3) We model discrimination performance by using discrimination thresholds instead of detection thresholds. The first psychophysical experiment tested the visual system's sensitivity as a function of spatial frequency, orientation, and average luminance. The second experiment tested the relation between contrast detection and contrast discrimination.