The traditional mean-squared-error or peak-signal-to-noise error measures are mainly focused on the pixel-by-pixel difference between the original and compressed images. Such metrics are improper for subjective quality or fidelity assessment, since human perception is very sensitive to correlations between adjacent pixels. In this work, we explore the Haar wavelet to model the space-frequency localization property of human visual system (HVS). It is shown that the physical contrast in different resolutions can be easily represented in terms of transform coefficients. We model HVS with the Haar filter with several visual mechanisms and develop a subjective quality measure which is more consistent with human observation experience.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.