Near-threshold perceptual distortion prediction based on optimal structure classification
Yucheng Liu, Jan P. Allebach · 2016
Perceptual distortion prediction at near-threshold level has many applications in general image/video processing tasks. This paper presents a computational model to predict the near-threshold perceptual distortions based on optimal structure classification. This model accounts for contrast sensitivity, light adaptation, and various masking effects of the human visual system (HVS), and automatically adapts to local image structures by a soft classification scheme using a Gaussian Mixture Model (GMM). The proposed model is trained and verified on the public CSIQ local masking database. We demonstrate a superior prediction performance of the proposed model compared to previous research.