CU splitting early termination based on weighted SVM

Abstract

High efficiency video coding (HEVC) is the latest video coding standard that has been developed by JCT-VC. It employs plenty of efficient coding algorithms (e.g., highly flexible quad-tree coding block partitioning), and outperforms H.264/AVC by 35–43% bitrate reduction. However, it imposes enormous computational complexity on encoder due to the optimization processing in the efficient coding tools, especially the rate distortion optimization on coding unit (CU), prediction unit, and transform unit. In this article, we propose a CU splitting early termination algorithm to reduce the heavy computational burden on encoder. CU splitting is modeled as a binary classification problem, on which a support vector machine (SVM) is applied. In order to reduce the impact of outliers as well as to maintain the RD performance while a misclassification occurs, RD loss due to misclassification is introduced as weights in SVM training. Efficient and representative features are extracted and optimized by a wrapper approach to eliminate dependency on video content as well as on encoding configurations. Experimental results show that the proposed algorithm can achieve about 44.7% complexity reduction on average with only 1.35% BD-rate increase under the “random access” configuration, and 41.9% time saving with 1.66% BD-rate increase under the “low delay” setting, compared with the HEVC reference software.