A new rate control method for hierarchical video coding in HEVC

Yoon, Yeo-Jin; Kim, Hoon; Jung, Soon-Heung; Jun, Dongsan; Kim, Younhee; Choi, Jin Soo; Ko, Sung-Jea

doi:10.1109/bmsb.2012.6264268

Cited by 12 publications

(6 citation statements)

References 3 publications

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“…The Q-domain model builds direct relationship between bitrate and QP. In [5], Cauchy-distribution-based R-Q model was used to determine QP. In [6], a Laplace-distribution-based CTU level RC algorithm for HEVC was proposed.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Frame-Level Rate Control Algorithm for High Efficiency Video Coding

Lin¹,

Zhang²,

Xiao³

et al. 2016

KSII TIIS

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In video coding, the goal of rate control (RC) is not only to avoid the undesirable fluctuation in bit allocation, but also to provide a good visual perception. In this paper, a novel frame-level rate control algorithm for High Efficiency Video Coding (HEVC) is proposed. Firstly a model that reveals the relationship between bit per pixel (bpp), the bitrate of the intra frame and the bitrate of the subsequent inter frames in a group of pictures (GOP) is established, based on which the target bitrate of the first intra frame is well estimated. Then a novel frame-level bit allocation algorithm is developed, which provides a robust bit balancing scheme between the intra frame and the inter frames in a GOP to achieve the visual quality smoothness throughout the whole sequence. Our experimental results show that when compared to the RC scheme for HEVC encoder HM-16.0, the proposed algorithm can produce reconstructed frames with more consistent objective video quality. In addition, the objective visual quality of the reconstructed frames can be improved with less bitrate.

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Section: Related Workmentioning

confidence: 99%

An Efficient Frame-Level Rate Control Algorithm for High Efficiency Video Coding

Lin¹,

Zhang²,

Xiao³

et al. 2016

KSII TIIS

View full text Add to dashboard Cite

show abstract

“…The MAD between original frame and reconstructed one has been introduced in [7] as represented in (2). In a different way, the RC has improved by considering a representation in the ρ domain [20] as proposed in [21] and by taking into account additional parameters, as the frame rate [22].…”

Section: Related Workmentioning

confidence: 99%

Region-of-interest based rate control scheme for high efficiency video coding

Meddeb

Cagnazzo

Pesquet‐Popescu

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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International audienceIn this paper, we propose a new rate control scheme designed for the newest high efficiency video coding (HEVC) standard, and aimed at enhancing the quality of regions of interest (ROI). Our approach allocates a higher bit rate to the region of interest while keeping the global bit rate close to the assigned target value. This algorithm is developed for a videoconferencing system, where the ROIs (typically, faces) are automatically detected and each coding unit is classified in a region of the interest map. This map is given as input to the rate control algorithm and the bit allocation is made accordingly. Experimental results show that the proposed scheme achieves accurate target bit rates and provides an improvement in the region of interest quality, both in objective metrics and based on subjective quality evaluation

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“…It has encompassed various video media services and applies not only to full high definition (FHD) but also to 4K/8K ultra-HD (UHD) [2]- [4]. Since the standard was released, many studies have been conducted for the sake of its advantages of visual quality improvement [5]- [7], computational complexity reduction [8]- [16], bitrate reduction [17], [18], and prospects as a future video coding standard [19]- [26]. Among many coding tools, rate-distortion optimization (RDO) in the HEVC software model (HM) [26]- [28] is used to improve its coding efficiency [30], [31].…”

Section: Introductionmentioning

confidence: 99%

Perceptual Adaptive Quantization Parameter Selection Using Deep Convolutional Features for HEVC Encoder

Marzuki

Sim

2020

IEEE Access

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In this paper, we propose a perceptual adaptive quantization based on a deep neural network on high efficiency video coding (HEVC) for bitrate reduction while maintaining subjective visual quality. The proposed algorithm adaptively determines frame-level QP values for different picture types of the hierarchical coding structure in HEVC by taking into account the high-level features extracted from the original and previously reconstructed pictures. A predefined model based on the visual geometry group (VGG-16) network is exploited to extract the high-level features for subjective visual characteristics. Furthermore, the Lagrange multiplier for each frame is also adaptively determined by involving the proposed features for deciding the appropriate parameter of the Lagrange multiplier that can be used for rate-distortion optimization during the encoding process. Experimental results reveal that the proposed perceptual adaptive QP selection can facilitate bitrate savings up to 65.73% and 47.68% and improve the BD-rate based on SSIM by approximately 20.68% and 14.27% under low-delay-P and random-access coding structures, respectively, with very minimal visual quality degradation when compared to HM-16.20 without adaptive QP selection. INDEX TERMS Adaptive quantization parameter, deep neural network, high efficiency video coding (HEVC), perceptual quantization parameter, VGG-16 network, video coding.

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A new rate control method for hierarchical video coding in HEVC

Cited by 12 publications

References 3 publications

An Efficient Frame-Level Rate Control Algorithm for High Efficiency Video Coding

An Efficient Frame-Level Rate Control Algorithm for High Efficiency Video Coding

Region-of-interest based rate control scheme for high efficiency video coding

Perceptual Adaptive Quantization Parameter Selection Using Deep Convolutional Features for HEVC Encoder

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