Multiple early-termination scheme for TZ search algorithm based on data mining and decision trees

Abstract

The latest video compression standards, such as the H.264/AVC and the High Efficiency Video Coding (HEVC), provide fast Motion Estimation (ME) algorithms in their reference software aiming at complexity reduction. Test Zone Search (TZS) is the state-of-the-art fast ME algorithm, currently deployed in the reference HEVC encoder due to its great coding efficiency. However, ME is still one of the main sources of complexity in HEVC. This paper proposes an early-termination scheme for TZS, called e-TZS, based on an extensive data mining process on ME attributes. The data mining process allowed identifying the most relevant information during the encoding process to build a set of decision tree models that terminate TZS in different steps of its execution. The e-TZS scheme was implemented in the HEVC reference software and achieved average decision precision of 94.2%. Experimental results showed an average complexity reduction of 62.53% in TZS, with a negligible BD-rate increase of only 0.49%, in comparison to the original algorithm.