An adaptive QP offset determination method for HEVC

Papadopoulos, Miltiadis Alexios; Zhang, Fan; Agrafiotis, Dimitris; Bull, David

doi:10.1109/icip.2016.7533155

Cited by 20 publications

(14 citation statements)

References 13 publications

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“…Nevertheless, the proposed approach still shows consistent overall bitrate savings across video groups at various spatial resolutions, with an average BD-rate values at 1.1% and 0.5% for JCTVC-L1100 and JCTVC-X0038 respectively. According to the results in [40], the use of fixed QP offset values does not provide optimum R-D performance for all types of content. More significant bitrate savings may therefore be possible if our Lagrange multiplier determination approach is combined with a content-based adaptive QP model.…”

Section: Test Results On Adaptive Qp Configurations For Hmmentioning

confidence: 98%

“…This differs from the recommended configurations in [33,39] and [35], where fixed QP offset values are used for different hierarchical B frame levels to improve overall rate-distortion (R-D) performance. Based on the recent work in [40], using constant QP offset values does not always offer optimum R-D performance for all types of content, and QP offset values in the HEVC reference encoder should be adapted based upon video content. Since the purpose of this paper is solely to investigate the influence of Lagrange multipliers on R-D performance, constant QP values are employed in our training process, as this eliminates the confounding influence of QP offset.…”

Section: A Experimental Methodologymentioning

confidence: 99%

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Rate-Distortion Optimization Using Adaptive Lagrange Multipliers

Zhang

Bull

2019

IEEE Trans. Circuits Syst. Video Technol.

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In current standardized hybrid video encoders, the Lagrange multiplier determination model is a key component in rate-distortion optimization. This originated some 20 years ago based on an entropy-constrained high-rate approximation and experimental results obtained using an H.263 reference encoder on limited test material. In this paper, we present a comprehensive analysis of the results of a Lagrange multiplier selection experiment conducted on various video content using H.264/AVC and HEVC reference encoders. These results show that the original Lagrange multiplier selection methods, employed in both video encoders, are able to achieve optimum rate-distortion performance for I and P frames, but fail to perform well for B frames. The relationship is identified between the optimum Lagrange multipliers for B frames and distortion information obtained from the experimental results, leading to a novel Lagrange multiplier determination approach. The proposed method adaptively predicts the optimum Lagrange multiplier for B frames based on the distortion statistics of recent reconstructed frames. After integration into both H.264/AVC and HEVC reference encoders, this approach was evaluated on 36 test sequences with various resolutions and differing content types. The results show consistent bitrate savings for various hierarchical B frame configurations with minimal additional complexity. BD savings average approximately 3% when constant QP values are used for all frames, and 0.5% when non-zero QP offset values are employed for different B frame hierarchical levels.

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Section: Test Results On Adaptive Qp Configurations For Hmmentioning

confidence: 98%

Section: A Experimental Methodologymentioning

confidence: 99%

Rate-Distortion Optimization Using Adaptive Lagrange Multipliers

Zhang

Bull

2019

IEEE Trans. Circuits Syst. Video Technol.

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“…In [22], inter-frame dependency was measured by energy of prediction residuals, then the optimal QP was determined by taking inter-frame dependency into the Lagrange cost function. In [23], the optimal QP was related to mean squared error (MSE), and optimal QP offset was adaptively updated according to MSE of P frames and MSE of B frames. Xu et al [24] statistically analysed inter-frame dependency between GOPs and introduced GOP level empirical QP offset.…”

Section: Introductionmentioning

confidence: 99%

Sub-Frame Layer Rate Distortion Optimization for High Efficiency Video Coding

Wei

Zhou

et al. 2020

IEEE Access

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This paper proposes a sub-frame layer RDO algorithm to further improve coding performance of low-delay hierarchical prediction structure in High Efficiency Video Coding. In the proposed algorithm, each frame is segmented into two sub-frames according to motion intensity, and a sub-frame layer is taken as a basic optimizing unit. An inter-frame dependency model is proposed to quantify inter-frame dependency of a frame or a sub-frame. The proposed inter-frame dependency model is composed of two parts, Laplace distribution based direct inter-frame dependency model and distortion propagation chain. The direct inter-frame dependency model is used to evaluate dependency caused by direct reference, and the distortion propagation chain shows the relationship between direct reference and indirect reference. With quantified inter-frame dependency, Lagrange optimization is then used to solve the optimal λ-QP pair for each sub-frame layer in frame layer 1 (L1) to frame layer 4 (L4). For frame layer 0 (L0), additional L0 frames are adaptively inserted according to inter-frame dependency of the previous L0 frame, and the optimal λ-QP pair for each sub-frame in L0 is solved using Lagrange optimization. When peak signal to noise ratio is used as quality criterion, the proposed algorithm achieves 7.0% and 7.0% bit-rate reduction with lowdelay_P_main (LDP) and lowdelay_main (LDB) configurations respectively; when structural similarity is used as quality criterion, the proposed algorithm achieves 13.3% and 13.1% bit-rate reduction with LDP and LDB configurations respectively. INDEX TERMS High efficiency video coding, hierarchical prediction structure, rate distortion optimization, sub-frame layer.

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“…The Rate-Distortion (RD) dependency between RA layers were also exploited in the QPC scheme of [12]. While in [13], texture content was taken into account to determine the GOP-level Qp offset. In Zhao's algorithm [14], the Qp allocation was formulated as a non-linear programming problem with layered dependency, which was further solved by Newton-Raphson method.…”

Section: Introductionmentioning

confidence: 99%

GOP Structure-Independent Quantization Parameter Cascading in Video Coding

Lin

et al. 2019

IEEE Access

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The popular lossy coding standards set unequal quantization parameter (Qp) values to its successive frames or slices aimed at minimizing its encoder distortion subject to a bitrate constraint. Nowadays, this Qp cascading (QPC) strategy is normally achieved by the derivation of an optimization problem with regard to the group-of-picture (GOP) structure of successive frames. In this paper, we propose to extract coding unit (CU)-level predicting information and project them to frame-level dependency with real-time neural networks. Thus, we successfully estimate and update the frame-level dependency in a GOP without prior knowledge to the GOP-level prediction structure. Finally, the dependency is utilized in adaptive QPC for diverse GOP structures. The experimental results on high efficiency video coding (H.265/HEVC) demonstrate the effectiveness of our proposed framework, which achieves adaptive QPC for both random access (RA) and low delay (LD) structures with superior rate-distortion (RD) performances. INDEX TERMS Video coding, quantization parameter (Qp), rate-distortion (RD), high efficiency video coding (H.265/HEVC).

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An adaptive QP offset determination method for HEVC

Cited by 20 publications

References 13 publications

Rate-Distortion Optimization Using Adaptive Lagrange Multipliers

Rate-Distortion Optimization Using Adaptive Lagrange Multipliers

Sub-Frame Layer Rate Distortion Optimization for High Efficiency Video Coding

GOP Structure-Independent Quantization Parameter Cascading in Video Coding

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