Intelligent rate control for MPEG-4 coders
MPEG coder can multiplex a set of independently-coded, arbitrarily-shaped video objects and transmit it through either fixed or variable rate channels such as internet, wireless or satellite communications. Some quality control algorithms should support the encoding process of the visual objects to obtain and maintain best picture quality under the constraints of the quality requirements and channel environments. This paper focuses on the design of the intelligent rate control algorithm via introducing global rate distortion (RD) model constructed by quadratic neural network, by evaluating data-driven pattern analysis rather than rate-distortion mathematical models. Proposed global RD model is very useful in case the characteristics of the video sequences are varying rapidly. The performances of the proposed algorithm are superior to those of the MPEG-4 VM5+ rate control based on the regression process using mathematical RD model, in comparison with the average bits per frame to satisfy the channel constraints, encoded peak signal-to-noise ratio (PSNR), and the number of frame skips.
rate control mpeg neural-net functional-link net image processing