Statistical learning based intra prediction in H.264

In this paper, we improve the performance of intra prediction and simplify mode decision procedure at the same time. For these works, we apply a statistical learning method such as Support Vector Machines for Regression (SVR) to improve the performance of current H.264 intra prediction via batch learning. In addition, we only use single Macro Block type and one intra prediction mode with high prediction performance to simplify mode decision procedure. In our knowledge, this work is the first approach to apply a statistical learning method for prediction of video sequences. Therefore, we introduce theoretical backgrounds of SVR, and show the possibility of this challenge for video compression. From the experimental results, statistical learning based intra prediction improves significantly the average Peak Signal-to-Noise Ratio of intra prediction than the performance of current H.264.