Content-Aware Fast Motion Estimation Algorithm

Abstract

In this paper, we propose the Content-Aware Fast Motion Estimation Algorithm (CAFME) that can reduce computation complexity of motion estimation (ME) in H.264/AVC while maintaining almost the same coding efficiency. Motion estimation can be divided into two phases: searching phase and matching phase. In searching phase, we propose the Simple Dynamic Search Range Algorithm (SDSR) based on video characteristics to reduce the number of search points (SP). In matching phase, we integrate the Successive Elimination Algorithm (SEA) and the integral frame to develop a new SEA for H.264/AVC video compression standard, called Successive Elimination Algorithm with Integral Frame (SEAIF). Besides, we also propose the Early Termination Algorithm (ETA) to early terminate the motion estimation of current block.

We implement the proposed algorithm in the reference software JM9.4 of H.264/AVC and the experimental results show that our proposed algorithm can reduce the number of search points about 93.1%, encoding time about 42%, while maintaining almost the same bitrate and PSNR.

Introduction

Block matching-based motion estimation (ME) and compensation is a fundamental process in international video coding standards, such as MPEG-1, MPEG-2, MPEG-4, ITU-T H.263, and H.264, which can efficiently remove temporal redundancy. Since an ME module is usually the most computational-intensive part in a typical video encoder (about 50–90% of the entire system), a efficient ME module is essential and vital.

In recent years, many fast motion estimation algorithms have been proposed. Some algorithms like Three-Step Search (TSS) [1] and Diamond Search (DS) [2], search the best matched blocks following a predefined search pattern to speed up the searching process. The Successive Elimination Algorithm (SEA) [3] is a lossless approach which can avoid unnecessary computation of the sum of absolute difference (SAD) and reduce the computation complexity while maintaining the same performance. The Window Follower Algorithm (WFA) [7] can dynamically adjust the size of the search window to avoid unnecessary computations. Since the video content varies dramatically, these algorithms do not always perform well for videos of various activities. The drawbacks and advantages of these algorithms are listed in Table 1.

In this paper, we propose the Content-Aware Fast Motion Estimation (CAFME) Algorithm to speed up the motion estimation considering the video content. The CAFME consists of the Simple Dynamic Search Range Algorithm (SDSR), Successive Elimination Algorithm with Integral Frame (SEAIF), and Early Termination Algorithm (ETA). The SDSR adjusts search range adaptively according to the motion activity of the video. The experiments show that the SDSR performs well for the video of different kinds of motion activity. The SEAIF is designed for saving the computing of block matching in motion estimation of H.264/AVC and the ETA could skip some search points in motion estimation by early termination of the searching process. Although the CAFME consists of the SDSR, SEAIF, and ETA, these three algorithms can be used independently. The experimental result shows that the proposed algorithms could reduce the computing time-of-motion estimation and maintain almost the same coding efficiency compared with Full Search.

The paper is organized as follows: Section 2 introduces the related background knowledge. In Section 3, we present how the Content-Aware Fast Motion Estimation Algorithm is designed and developed. Section 4 reports the significant experimental results. Finally, the conclusions and future works are given in Section 5.