Composite-Block Model and Joint-Prediction Algorithm for Inter-Frame Video Coding

Rong Ding, Fan Wang, Qionghai Dai, Wenli Xu, Dongdong Zhu

Abstract: Block-matching algorithm (BMA) is widely adopted in video coding. However, many blocks contain both background pixels and moving-object pixels, which often differ significantly in true physical motions. Using BMA for these blocks may lead to large prediction error and thus decreased coding efficiency. More accurate prediction can be achieved by object-based coding, which segments a video frame into different objects and codes these objects separately. However, additional bits are required for encoding the shape of the objects, and the computation complexity of object segmentation is often very high. In this paper, a composite-block model and a joint-prediction algorithm are proposed. This algorithm can get accurate prediction without shape coding, and its computation complexity is very close to that of the BMA. The experimental result shows that the new H.264 coder enhanced by our algorithm outperforms original H.264 coder by approximately 0.8~1.5 dB