Intracoding and Refresh With Compression-Oriented Video Epitomic Priors

Qijun Wang, Ruimin Hu, Zhongyuan Wang

Abstract: In video compression, intracoding plays an important role in terms of coding efficiency and error resilience and has been an attractive research topic since the standardization of H.264/AVC. In this paper, we propose a high-performance intracoding scheme with the help of epitomic priors. Different from intracoding in H.264/AVC and other video standards, we construct image epitomes as coding priors and use them to generate predictions of intrablocks at the encoder. In addition, we losslessly code and transmit the image epitomes to the decoder. We perform compression-oriented video epitomic analysis and search for the best epitomic priors by using the expectation maximization algorithm. The resulting image epitomes for a video sequence can be viewed as the base layer in spatially scalable video coding. Experiments show that our proposed intracoding scheme improves the state of the art by an average of 0.53 dB in PSNR. Simulations under a packet loss environment also demonstrate that intrarefresh with epitomic priors outperforms random intrarefresh by up to 2 dB, leading to better subjective quality.