Human observer responses to progressively compressed images

Mean squared error (MSE) and peak signal-to-noise-ratio (PSNR) are the most common methods for measuring the quality of compressed images, despite the fact that their inadequacies have long been recognized. Quality for compressed still images is occasionally evaluated using human observers who provide subjective ratings of the images. Both SNR and subjective quality judgments, however may be inappropriate for evaluating progressive compression methods which are to be used for fast browsing applications. In this paper we present a novel experimental and statistical framework for comparing progressive coders. The comparisons use response time studies in which human observers view a series of progressive transmissions, and respond to questions about the images as they become recognizable. We describe the framework and apply it to the comparison of several well known progressive algorithms.