Hybrid Model Based Coding Enhancement for MPEG

The novelty of our approach lies in the fact that it helps in the fully synthetic prediction of the first frames which occur after scene change. This prediction helps in reduction of size of the frames and in total bits. We have found that the high Signal to-Noise Ratio (SNR) of the Model can result in improving the SNR of the first frame. This high SNR of first frame further helps in reducing the size of the subsequent frames. The prediction is done well when there is a less difference between the Model and the incoming first frame. We have also found that significant reduction can be achieved for the input video sequence which has scene change or complex environment by providing multiple Models corresponding to each object in the input video.

We have found that the reduction is highest when the Model and the object are at the same position and aligned in one direction. We have found that by using highly professional renderer, the reduction can be achieved for real video sequences as well. We have shown the visual effects which have indicated where the content is encoded Model based and where it is traditionally encoded. It has been found that by enhancing MPEG-4 with MBC results in the reduction of the total bits which are required for video transmission because the decoder can make use of Model information which it has already. Hence, this information is not required to be transmitted again every time. We have found that the decreased bitrate has not come at the cost of visual quality as can be seen from the Peak Signal-to-Noise Ratio (PSNR) values of luma and chroma components.