Video Processing for Human Perceptual Visual Quality-Oriented Video Coding

We have developed a video processing method that achieves human perceptual visual quality-oriented video coding. The patterns of moving objects are modeled by considering the limited human capacity for spatial-temporal resolution and the visual sensory memory together, and an online moving pattern classifier is devised by using the Hedge algorithm. The moving pattern classifier is embedded in the existing visual saliency with the purpose of providing a human perceptual video quality saliency model. In order to apply the developed saliency model to video coding, the conventional foveation filtering method is extended. The proposed foveation filter can smooth and enhance the video signals locally, in conformance with the developed saliency model, without causing any artifacts. The performance evaluation results confirm that the proposed video processing method shows reliable improvements in the perceptual quality for various sequences and at various bandwidths, compared to existing saliency-based video coding methods.