16 September 1994 Adaptive perceptual quantization using a neural network for video coding
Author Affiliations +
Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.185897
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States
Abstract
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 Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Byung-Sun Choi, Byung-Sun Choi, H. D. Cho, H. D. Cho, Kyoung Won Lim, Kyoung Won Lim, Kangwook Chun, Kangwook Chun, Jong Beom Ra, Jong Beom Ra, } "Adaptive perceptual quantization using a neural network for video coding", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185897; https://doi.org/10.1117/12.185897
PROCEEDINGS
10 PAGES


SHARE
Back to Top