Temporal-Layer-Motivated Lambda Domain Picture Level Rate Control for Random-Access Configuration in H.265/HEVC

Yan, Gao; Wan, Shuai; Yang, Kaifang; Wu, Hong Ren; Liu, Ying

doi:10.1109/tcsvt.2017.2769703

Cited by 25 publications

(8 citation statements)

References 21 publications

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“…The original studies [2,3] claimed that these values were provided based on video content. However, studies have discovered [30][31][32] that the existing R-λ model in the HM software is not optimal for the coding structure for the RA configuration.…”

Section: Current State Of the R−𝛌 Modelmentioning

confidence: 99%

Deep Convolutional Feature-Driven Rate Control for the HEVC Encoders

et al. 2021

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This work proposes a rate control model based on deep convolutional features to improve the video coding performance of the HEVC encoders under the random access (RA) configuration. The proposed algorithm extracts high-level features from the original and previous coded frames using a pretrained visual geometry group (VGG-16) model by considering characteristics of a different temporal layer for the RA configuration. Subsequently, R-λ parameters (alpha and beta), bit allocation, λ estimation, and quantization parameter decision at frame-level are formulated by utilizing the extracted high-level features to maintain video quality and bitrate accuracy control. In addition, bit allocation at the group-of-picture (GOP)-level rate control is proposed with perceptual-based thresholding to control smooth bitrates and visual quality between adjacent GOPs. The results verify that the proposed algorithm is efficient in coding performance and bit accuracy by keeping visual quality. Compared with the existing R-λ rate model in HM-16.20, the proposed models can achieve an average BD-rate gain of -4.39% and -8.74% in PSNR and MSSSIM metrics for the RA configuration, respectively.INDEX TERMS Deep neural network, high efficiency video coding (HEVC), perceptual video coding, rate control, video coding

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Section: Current State Of the R−𝛌 Modelmentioning

confidence: 99%

Deep Convolutional Feature-Driven Rate Control for the HEVC Encoders

et al. 2021

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“…As this paper targets the off-line application, the R-D performance is the most important consideration. And RA encoding mode could achieve superior R-D performance than intra-only and low-delay encoding modes, due to the RA mode's more effective inter picture prediction [42]. Therefore, all the testing sequences are encoded with RA mode, configured with encoder_randomaccess_main_scc.cfg.…”

Section: A Experimental Designmentioning

confidence: 99%

Down-Sampling Based Rate Control for Mobile Screen Video Coding

Tang

Yang

et al. 2019

IEEE Access

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With the improvement of hardware capability of mobile devices, mobile devices are more and more widely used. Mobile screen video recording is one of the important applications. However, the generated video files will occupy plenty of memory resources, which are limited in mobile devices. Fortunately, a well designed video coding method could effectively relieve such pressure. Therefore, aimed at the mobile screen video, this paper proposes a down-sampling based rate control algorithm to improve the compression efficiency. Firstly, the source video is down sampled by a factor of 4. Then, the down sampled video is encoded twice and the coding information is stored. Finally, based on the stored coding information, the real encoding process is optimized at bit allocation and bit control. Experimental results show that compared with the default rate control method in high efficiency video coding test model, the proposed method could obviously improve rate distortion performance and bit control accuracy.INDEX TERMS Rate control, video coding, mobile, screen content, HEVC.

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“…In [4], SATD is taken as the measurement of complexity, which ignores the relevant characteristics of video content. In [5], differential histograms are adopted to measure the complexity of CTU, which has the uncertainty of the selection for threshold in different video sequences. e above algorithms improve the accuracy of complexity of CTU to a certain extent, but the overall performance of rate control algorithms is not improved obviously.…”

Section: Introductionmentioning

confidence: 99%

Optimized Rate Control Algorithm of High-Efficiency Video Coding Based on Region of Interest

Song

Zhang

2020

Journal of Electrical and Computer Engineering

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Aiming at the problems that the strategy of target bit allocation at the CTU layer has deviations from the human subjective observation mechanism, and the update phase of parametric model has a higher complexity in the JCTVC-K0103 rate control algorithm of ITU-T H.265/high efficiency video coding (HEVC) standard. Optimized rate control (ORC) algorithm of ITU-T H.265/HEVC based on region of interest (ROI) is proposed. Firstly, the algorithm extracts the region of interest of video frames based on time and space domains by using the improved Itti model. Then, the weight of target bits w is recalculated based on space-time domains to improve the rate control accuracy, and the target bits are distributed based on ROI by the adaptive weight algorithm once again to make the output videos more attuned with the human visual attention mechanism. Finally, the quasi-Newton algorithm is used to update the rate distortion model, which reduces the computational complexity in the update phase of the parametric model. The experimental results show that the ORC algorithm can obtain a better subjective quality in the compressed results with less bit error compared with the other two algorithms. Meanwhile, the rate distortion performance of the ORC algorithm is better on the premise of guaranteeing rate control performance.

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Temporal-Layer-Motivated Lambda Domain Picture Level Rate Control for Random-Access Configuration in H.265/HEVC

Cited by 25 publications

References 21 publications

Deep Convolutional Feature-Driven Rate Control for the HEVC Encoders

Deep Convolutional Feature-Driven Rate Control for the HEVC Encoders

Down-Sampling Based Rate Control for Mobile Screen Video Coding

Optimized Rate Control Algorithm of High-Efficiency Video Coding Based on Region of Interest

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