Despite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tools, Multiple Transform Selection (MTS) require the best of several transforms to be obtained using the Rate-Distortion Optimization (RDO) process, which increases the time spent video encoding, meaning that VVC is not suited to real-time sensor application networks. In this paper, a low-complexity multiple transform selection, combined with the multi-type tree partition algorithm, is proposed to address the above issue. First, to skip the MTS process, we introduce a method to estimate the Rate-Distortion (RD) cost of the last Coding Unit (CU) based on the relationship between the RD costs of transform candidates and the correlation between Sub-Coding Units’ (sub-CUs’) information entropy under binary splitting. When the sum of the RD costs of sub-CUs is greater than or equal to their parent CU, the RD checking of MTS will be skipped. Second, we make full use of the coding information of neighboring CUs to terminate MTS early. The experimental results show that, compared with the VVC, the proposed method achieves a 26.40% reduction in time, with a 0.13% increase in Bjøontegaard Delta Bitrate (BDBR).
Today, 360°video has become an integral part of people's lives. Despite the fact that the latest generation standard Versatile Video Coding (VVC) demonstrates a significant gain in encoding capacity over High Efficiency Video Coding (HEVC), it still has room for 360°video encoding improvements. To further enhance the applicability of 360°video coding, an optimized rate control (RC) algorithm in VVC for 360°video is proposed in this paper. We present an efficient extraction algorithm for obtaining the video's saliency feature. Furthermore, for the characteristics of 360°video, a partitioning algorithm is also proposed to divide a frame into demand and non-demand regions. Additionally, to achieve precise and rational RC, a Coding Tree Unit (CTU)-level bit allocation strategy is proposed based on the saliency feature for the above-mentioned regions. The experimental results show that the proposed RC algorithm can achieve 11.77 % bitrate savings and more accurate allocation compared with the default algorithm of VVC. Also, performance enhancement has been observed in comparison to the most advanced algorithm.
This paper presents a high-performance rate control (HPRC) algorithm for the Versatile Video Coding (VVC) standard that aims to achieve higher coding efficiency by considering spatial and temporal feature complexity. The HPRC algorithm differs from conventional rate control (RC) algorithms in that it uses an adaptive Canny operator (ACO) with a novel doublethreshold algorithm to obtain the feature complexity of video content accurately. Moreover, an advanced bit allocation strategy at the frame-level and coding tree unit (CTU)-level is constructed to realize rational RC by thoroughly exploring the relationship between coding bits and complexity. To improve the precision of RC, an appropriate parameter updating based on the quasi-Newton algorithm is also proposed. Experimental results demonstrate that the proposed HPRC algorithm outperforms the default RC algorithm in VVC Test Model (VTM) 18.0, with Bjøntegaard Delta Rate (BD-Rate) savings of 8.77 % and 10.34 % under Low Delay P and Random Access configurations, respectively. Furthermore, the proposed algorithm also shows performance enhancements compared to other advanced algorithms.
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