Efficient AMP decision and search range adjustment algorithm for HEVC

Abstract

The advanced video encoder High Efficiency Video Coding (HEVC) utilizes several novel coding tools so that it can obtain improvement in coding performance for a huge number of video data. However, these tools increase the computational complexity greatly specially in the interprediction phase. Therefore, optimization for interprediction plays an important role in accelerating the whole HEVC encoding process. To this end, this paper proposes an efficient prediction algorithm for improving HEVC intercoding. According to the spatial correlation between the current block and its co-located block in the previous frame, we design a fast decision method so as to perform asymmetric partitions directly without the complicated calculation. Furthermore, based on the motion degree function we defined, the motion search range of motion estimation can be adaptively adjusted. Experimental results demonstrate that the proposed algorithm is able to save coding time significantly both under RandomAccess and Lowdelay P configurations, with a negligible drawback in term of Bjontegaard delta-rate increase.

Fast inter-prediction algorithm based on motion vector information for high efficiency video coding

“…Table 3 describes the sequence information, including different resolutions, numbers of frames, and frame rates (FPS). We use (11) to compute time-saving and evaluate the coding efficiency by BDBR and BDPSNR [26,27] Table 4, the proposed algorithm saves 43.85% of the average coding time, which is better than 41.99% of the average coding time in [19]. The method in [19] is without CU early split, and early terminates the PU prediction only by motion vector and residual, so it will lead to the rising BDBR and less time-saving in the sequences with small resolution and high motion, such as Class D. Figure 16 draws the RD curve comparison of HM.16.3, the proposed method, and [19] for PartyScene (S10) sequence.…”

“…In [10], the CU splitting optimization is viewed as a classification task and solved by the weighted Support Vector Machine (SVM). Huang et al [11] efficiently switch AMP by posterior probability analysis and adaptively adjust the search range by motion degree. Huang et al [12] predict the CU depth range from neighboring CTUs.…”

Learning adaptive motion search for fast versatile video coding in visual surveillance systems

“…where ET proposal and ET VVC are the ET with the proposed VVC codec and the standard VVC codec, respectively. Two relevant adaptive motion search methods, proposed in [23] and [24], are used as the relevant competitors. It should be noted that Huang et al proposed an ASR method for HEVC codec in [23] where pre-set SR values are selected using an assessment of motion degree.…”

“…Two relevant adaptive motion search methods, proposed in [23] and [24], are used as the relevant competitors. It should be noted that Huang et al proposed an ASR method for HEVC codec in [23] where pre-set SR values are selected using an assessment of motion degree. For a fair comparison, we have implemented this ASR method for the same VVC reference software and selected an optimized set of thresholds.…”

“…Search range adaptation is a sub-case of adaptive motion search which has also been considered a promising solution to achieve low-complexity video coding. In an early work, Huang et al proposed in [23] an adaptive search range (ASR) solution for low-complexity HEVC. In this method, the search range (SR) of current CU is selected among four pre-set candidates based on a measurement of motion degree.…”