Adaptive perceptual quantization using a neural network for video coding

This paper describes a new adaptive quantization algorithm for video sequence coding, which can reflect perceptual characteristics of macroblocks by using a neural network classifier. Multilayer perceptron is adopted as a neural network structure, and the feature parameters and target classes of training macroblocks are prepared for learning. The coding performance based on the neural network classifier is investigated by computer simulation. In comparison with both the non-adaptive quantization scheme and the adaptive one in the MPEG-2 TM5, the proposed scheme is proven to enhance perceptual quality in video coding.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.