A new DCT-based just-noticeable distortion estimator for images

Abstract

Just-noticeable distortion (JND) based on human visual characteristics provides a good means to reflect the tolerance of image distortion with respect to human observers, for both data compression and quality measurement. In this paper, various existing JND models are surveyed and the typical models are benchmarked based on a uniform criterion. A new model is then developed and tested for different types of images. Experiments and the associated subjective tests show the improved performance of the proposed scheme over the existing models for luminance adaptation (especially in dark regions) and masking effect in edge regions.