Rate Control for H.264 Video With Enhanced Rate and Distortion Models

Kwon, Do-Kyoung; Shen, Mei-Yin; Kuo, C.-C. Jay

doi:10.1109/tcsvt.2007.894053

Cited by 218 publications

(107 citation statements)

References 28 publications

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“…PSNR peak = (0.03 × PSNR full × (α − 0.5)) + PSNR full (6) Based on the linear model in (2), sa peak is calculated within the range from 0.1 to 1 as…”

Section: Equation (2)mentioning

confidence: 99%

“…Thus, an inadequate QP may be selected. For improved coding efficiency, enhanced distortion models [2][3][4][5][6] are developed and rate-distortion (R-D) model is optimized or contents-aware bit allocation is proposed [5][6][7][8][9][10]. A number of recent approaches incorporate characteristics of the human visual system (HVS) into bitrate control.…”

Section: Introductionmentioning

confidence: 99%

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Bitrate control using a heuristic spatial resolution adjustment for a real-time H.264/AVC encoder

Rhee

Kim

Lee

2012

EURASIP J. Adv. Signal Process.

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Conventional bitrate control algorithms that change only the quantization parameter (QP) often suffer from quality degradation when the target bitrate is very low. Therefore, rate control algorithms that adjust spatial resolution in addition to QP control have recently been proposed, but their computations are too complex to be processed in real time. This research proposes a very simple, but effective, rate control algorithm that employs spatial resolution control as well as the existing QP-based bitrate control. The spatial resolution ratio for the best peak signal-to-noise ratio (PSNR) is calculated using a simple estimation model which defines the relationship between the PSNR and the spatial resolution at very low bitrate compression. In the proposed bitrate control algorithm, two scalability tools for adjusting the QP and the spatial resolution ratio are used sequentially to reach the target PSNR and the control decision is made for a group of pictures. Experimental results show that the proposed bitrate control algorithm approximates an optimal solution and yields a better subjective quality as well as objective quality at various bitrates compared to the conventional QP-based bitrate control algorithm. The decision of the control parameters requires very small computational complexity and is made in a completely automatic manner so that the proposed algorithm is well suited for real-time applications.

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“…PSNR peak = (0.03 × PSNR full × (α − 0.5)) + PSNR full (6) Based on the linear model in (2), sa peak is calculated within the range from 0.1 to 1 as…”

Section: Equation (2)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bitrate control using a heuristic spatial resolution adjustment for a real-time H.264/AVC encoder

Rhee

Kim

Lee

2012

EURASIP J. Adv. Signal Process.

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“…In [9], a rate control technique for offline processing using a video quality metric and evolution strategy was proposed; however, this scheme is still computationally complex. In [10], a rate model for header bits is developed and a two-stage encoding process is proposed to improve the rate control. Many other studies have been done on rate control and a recent survey of these studies is provided in [11].…”

Section: Related Studymentioning

confidence: 99%

FMO-based H.264 frame layer rate control for low bit rate video transmission

Cajote

Aramvith

Miyanaga

2011

EURASIP J. Adv. Signal Process.

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The use of flexible macroblock ordering (FMO) in H.264/AVC improves error resiliency at the expense of reduced coding efficiency with added overhead bits for slice headers and signalling. The trade-off is most severe at low bit rates, where header bits occupy a significant portion of the total bit budget. To better manage the rate and improve coding efficiency, we propose enhancements to the H.264/AVC frame layer rate control, which take into consideration the effects of using FMO for video transmission. In this article, we propose a new header bits model, an enhanced frame complexity measure, a bit allocation and a quantization parameter adjustment scheme. Simulation results show that the proposed improvements achieve better visual quality compared with the JM 9.2 frame layer rate control with FMO enabled using a different number of slice groups. Using FMO as an error resilient tool with better rate management is suitable in applications that have limited bandwidth and in error prone environments such as video transmission for mobile terminals.

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“…The optimization of bit allocation among dependent sources is computationally complex and difficult to use in practical encoding [2]. Most optimization methods assume independent sources, e.g., GOPs in a sequence, or the BUs in an inter-frame [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

A Study on Consistency between MINAVE and MINMAX in SSIM Based Independent Perceptual Video Coding

Wang

Mou

Zhang

2015

IEICE Trans. Inf. & Syst.

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SUMMARYIn this letter, we study the R-D properties of independent sources based on MSE and SSIM, and compare the bit allocation performance under the MINAVE and MINMAX criteria in video encoding. The results show that MINMAX has similar results in terms of average distortion with MINAVE by using SSIM, which illustrates the consistency between these two criteria in independent perceptual video coding. Further more, MINMAX results in lower quality fluctuation, which shows its advantage for perceptual video coding. key words: optimal bit allocation, MINAVE, MINMAX, perceptual video coding

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Rate Control for H.264 Video With Enhanced Rate and Distortion Models

Cited by 218 publications

References 28 publications

Bitrate control using a heuristic spatial resolution adjustment for a real-time H.264/AVC encoder

Bitrate control using a heuristic spatial resolution adjustment for a real-time H.264/AVC encoder

FMO-based H.264 frame layer rate control for low bit rate video transmission

A Study on Consistency between MINAVE and MINMAX in SSIM Based Independent Perceptual Video Coding

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