Improving the performance of MPEG compatible encoders using on line retrainable neural networks

On line retraining of neural network is introduced for extracting foreground/background objects in video sequences. The scheme is applied together with a modification of the rate control of MPEG-1 algorithm. The proposed method is compatible to MPEG-1/2 standard but also can be used as a pre-coding stage for the forthcoming MPEG-4 algorithm. Simulation studies have shown an improvement of about 1.5 dB on average as far the PSNR is concerned compared with the conventional MPEG-1 encoder.