Abstract
The High Efficiency Video Coding (HEVC) standard has now become the most popular video coding solution for video conferencing, broadcasting, and streaming. However, its compression performance is still a critical issue for adopting a large number of emerging video applications with higher spatial and temporal resolutions. To advance the current HEVC performance, we propose an efficient temporal rate allocation solution. The proposed method adaptively allocates the compression bitrate for each coded picture in a group of pictures by using a trellis-based dynamic programming approach. To achieve this task, we trained the trellis-based quantization parameter for each frame in a group of pictures considering the temporal layer position. We further improved coding efficiency by incorporating our proposed framework with other inter prediction methods such as a virtual reference frame. Experiments showed around 2% and 5% bitrate savings with our trellis-based rate allocation method with and without a virtual reference frame compared to the conventional HEVC standard, respectively.
Highlights
High Efficiency Video Coding (HEVC) controls bits for each frame in a group of pictures (GOP) with a temporal index associated with its hierarchical reference model by adjusting the quantization parameter for each frame so that high Tid frames are encoded at a higher quantized parameter (QP)
The HEVC with trellis-based rate allocation proposed (TRA) and Virtual reference frame (VRF) methods achieved a significant coding improvement for all test sequences, notably by 5.2% and 2.7% of Based on the bitrate reduction rate (BDBR) on average for the low and high rates regions, respectively; The TRA method provides around 1.55% and 0.82% of BDBR saving for test seThe TRA method provides around 1.55% and 0.82% of BDBR saving for test sequences quences at the low and high rate regions, respectively, while the VRF method proat the low and high rate regions, respectively, while the VRF method provides around vides around 3.32% and 1.86% of BDBR saving; 3.32% and 1.86% of BDBR saving; The proposed methods, both TRA and VRF, achieve better compression performance
Meanon the decoded information available at both the encoder and decoder; no syntax while, the motion vector refinement (MVR) can partly reduce the quantization noise and blocking artifacts in interelements need torefining changethe in the standard specification, no overhead bitrate needs to polated pictures by adaptively obtained in the hierarchical motion estimation (HME).and
Summary
The wide growth of multimedia applications always demands more powerful video transmission over the internet with high compression performance as well as low complexity. There is still a demand for beyond HEVC coding to meet emerging requirements of higher resolutions (i.e., 4K, 8K) and diverse contents (screen contents, drone, etc.) In this context, in the newest video compression standard, H.266/Versatile Video Coding (VVC), many coding tools have been proposed, such as partitioning with quad-tree plus binary, adaptive transforms, new intra modes, affine motion estimation, dependent quantization, etc. For each GOP, HEVC and VVC classified frames into a temporal index (Tid), and depending on their hierarchical location and frame types (i.e., intra or inter), the quantized parameter (QP) is adjusted by a fixed value This framework is very simple and easy to validate the performance of coding tools during the standardization process. HEVC controls bits for each frame in a group of pictures (GOP) with a temporal index associated with its hierarchical reference model by adjusting the quantization parameter for each frame so that high Tid frames are encoded at a higher QP. There are many works on VRF, there is lacking investigation on the impact of virtual frames on coding performance
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