Mode Refinement Algorithm for H.264 Inter Frame Requantization

Lefol, Damien; Bull, David

doi:10.1109/icip.2006.312534

Cited by 11 publications

(9 citation statements)

References 10 publications

(7 reference statements)

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“…In [23], the statistical properties of the mode distribution are utilized for fast mode refinement of intra prediction. Similarly, in [24] the statistical properties of the mode distribution and motion vector refinement were exploited to reduce the complexity of inter prediction. Given the differences between HEVC and previous video coding standards in their block structure, motion estimation and residual information coding, traditional transrating techniques cannot be directly applied to HEVC.…”

Section: A Fast Transcoding Techniquesmentioning

confidence: 99%

Efficient Bit Rate Transcoding for High Efficiency Video Coding

Van

Praeter

Wallendael

et al. 2016

IEEE Trans. Multimedia

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Abstract-High efficiency video coding (HEVC) shows a significant advance in compression efficiency and is considered to be the successor of H.264/AVC. To incorporate the HEVC standard into real-life network applications and a diversity of other applications, efficient bit rate adaptation (transrating) algorithms are required. A current problem of transrating for HEVC is the high computational complexity associated with the encoder part of such a cascaded pixel domain transcoder. This paper focuses on deriving an optimal strategy for reducing the transcoding complexity with a complexity-scalable scheme. We propose different transcoding techniques which are able to reduce the transcoding complexity in both CU and PU optimization levels. At the CU level, CUs can be evaluated in top-to-bottom or bottom-to-top flows, in which the coding information of the input video stream is utilized to reduce the number of evaluations or to early terminate certain evaluations. At the PU level, the PU candidates are adaptively selected based on the probability of PU sizes and the co-located input PU partitioning. Moreover, with the use of different proposed methods, a complexity-scalable transrating scheme can be achieved. Furthermore, the transcoding complexity can be effectively controlled by the machine learning based approach. Simulations show that the proposed techniques provide a superior transcoding performance compared to the state-of-the-art related works. Additionally, the proposed methods can achieve a range of trade-offs between transrating complexity and coding performance. From the proposed schemes, the fastest approach is able to reduce the complexity by 82% while keeping the bitrate loss below 3%.Index Terms-Bit rate adaptation, complexity scalable transcoding, high efficiency video coding (HEVC), machine learning.

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Section: A Fast Transcoding Techniquesmentioning

confidence: 99%

Efficient Bit Rate Transcoding for High Efficiency Video Coding

Van

Praeter

Wallendael

et al. 2016

IEEE Trans. Multimedia

View full text Add to dashboard Cite

show abstract

“…Otherwise stated, we examine architectures that improve ratedistortion performance of the open-loop transcoder, at complexity lower than the CPDT transcoder. Architectures that refine mode information and motion vectors, hence having higher complexity than the CPDT transcoder, have been studied in among others [8] and [9]. This was discussed for example in [6].…”

Section: Non-linear Operationsmentioning

confidence: 99%

“…In literature, fast architectures for H.264/AVC transcoding are mostly based on the CPDT architecture, while single-loop architectures were mentioned as not to be useful in practical applications [8,9,15]. These results were based To tackle both spatial and temporal drift terms, this architecture can be extended to the hybrid requantization transcoding architecture as shown in Fig.…”

Section: Single-loop Architectures With Spatial Compensationmentioning

confidence: 99%

“…Different fast motion estimation algorithms have been proposed. Mode refinement for a cascaded decoderencoder in requantization transcoding was for example discussed in [8,9]. Solutions for spatial resolution reduction [10][11][12] or heterogeneous transcoding from or to H.264/AVC [13,14] also focused on pixel-domain cascaded decoderencoder solutions.…”

Section: Introductionmentioning

confidence: 99%

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Requantization transcoding for H.264/AVC video coding

Cock

Notebaert

Lambert

et al. 2010

Signal Processing: Image Communication

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In this paper, efficient solutions for requantization transcoding in H.264/AVC are presented. By requantizing residual coefficients in the bitstream, different error components can appear in the transcoded video stream. Firstly, a requantization error is present due to successive quantization in encoder and transcoder. In addition to the requantization error, the loss of information caused by coarser quantization will propagate due to dependencies in the bitstream. Because of the use of intra prediction and motion-compensated prediction in H.264/AVC, both spatial and temporal drift propagation arise in transcoded H.264/AVC video streams. The spatial drift in intra-predicted blocks results from mismatches in the surrounding prediction pixels as a consequence of requantization. In this paper, both spatial and temporal drift components are analyzed. As is shown, spatial drift has a determining impact on the visual quality of transcoded video streams in H.264/AVC.In particular, this type of drift results in serious distortion and disturbing artifacts in the transcoded video stream. In order to avoid the spatially propagating

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“…In transcoder, if the target frame size and frame rate are not changed, re-quantization can also achieve low bitrate (Werner, 1999;Cock et al, 2006;Lefol and Bull, 2006). The block mode adopted in higher quantization parameter (QP) is different from the mode in lower QP.…”

Section: Introductionmentioning

confidence: 99%

Intra mode selection in downsizing video transcoder based on H.264

Liu

Wang

2009

Int J Imaging Syst Tech

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An intra mode selection scheme is proposed in this work, which supports both downsizing transcoding and re-quantization transcoding simultaneously. In the proposal, a total number of nonzero coefficients in precoded frame is used as criterion and a thresholding method is applied to select intra macroblock mode in reencoder. To calculate this threshold, which is related to re-quantization parameter (denoted as Q r ), we propose a Th_I-Q r model which includes direct method and percentage I16MB method. In the former, an exponent model is proposed to describe relationship between the threshold and the Q r ; while in the latter, the threshold Th_I is converted into percentage of macroblocks with I16MB mode in the downsized frame (denoted as per_16), and relationship between the per_16 and the Q r is also modeled as an exponent function. Then the two exponent models are all converted into linear regression model, and least square estimation is used to estimate the parameters of the models. Furthermore, if I4MB mode is selected for one macroblock, the intra prediction modes in precoded frame are utilized to select prediction mode for every 4 3 4 block of the macroblock in downsized frame to reduce computational complexity. We compared rate distortion performance and computational complexity of the proposed method with rate-distortion optimization method. Simulation results demonstrate that on the precondition of compression performance of the proposal being close to the results of the rate-distortion optimization method, the proposed method can save up to 30 and 80% in total encoding time and mode decision time, respectively. V

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Mode Refinement Algorithm for H.264 Inter Frame Requantization

Cited by 11 publications

References 10 publications

Efficient Bit Rate Transcoding for High Efficiency Video Coding

Efficient Bit Rate Transcoding for High Efficiency Video Coding

Requantization transcoding for H.264/AVC video coding

Intra mode selection in downsizing video transcoder based on H.264

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