Gabor difference analysis of digital video quality

The rapid increase in the development of digital video systems has generated a strong need for objective video quality metrics. The compression, storage and transmission of digital video systems have different properties from that of traditional analog systems, thus introduce different impairments. Traditional analog methods are not suited to the quality analysis of digital videos.; The focus of this work is to adaptively model the human visual perception system in the role of subjective video quality evaluation using features derived from psycho-perceptual studies. Two models are presented in this work. One is the Gabor Difference Analysis (GDA) full reference model, and the other is the Reverse Frame Prediction (RFP) no reference video quality model. Both models are based on the multi-channel properties of the human visual system. Gabor filtering is used in both models. In the GDA model, a reference and a degraded digital video sequence are compared by taking into account the properties of the human visual system. The RFP model does not need a reference video. This model is intended for in-service testing and is designed for online monitoring.; The evaluation of the performance of the proposed models is carried out. The models in this work are shown to be consistent with the data from subjective test over a wide range of scenes. This work is critical to the evaluation of the effectiveness of compression schemes on HDTV imagery.