An efficient Lagrangian multiplier selection method based on temporal dependency for rate–distortion optimization in H.265/HEVC

Yang, Kaifang; Wan, Shuai; Yan, Gao; Wu, Hong Ren; Feng, Yan

doi:10.1016/j.image.2017.05.006

Cited by 12 publications

(9 citation statements)

References 21 publications

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“…In addition, we implement Yang's algorithm [8], which is a Lagrangian multiplier optimization method, and combine it with our algorithm. The results are shown in Table 4, which confirm that our algorithm can further improve the overall RD performance when combining with other RDO algorithms at different encoder levels, such as Lagrangian multiplier optimization.…”

Section: Resultsmentioning

confidence: 99%

“…All the above standards are lossy coding standards with Rate-Distortion Optimization (RDO), an optimal tradeoff between coding bitrates and quality. Recently, different types of RDO methods, such as Lagrange multiplier optimization [4]- [8], Quantization parameter Cascading (QPC) approach, and perceptual-driven optimization, have been developed at different video encoder levels. Among them, QPC approach allocates different Quantization parameters (Qps) to every hierarchy of video, such as Group-Of-Pictures (GOPs), frames, Coding Units (CUs), and so on.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

GOP Structure-Independent Quantization Parameter Cascading in Video Coding

Lin

et al. 2019

IEEE Access

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“…Equation 20is the general rule to describe impact of distortion of one frame on distortion of the other frame. Comparing (16), (18) and (19), the total impact of distortion of p 0 on distortion of its following frames is a combination of direct impact DI dis . In a similar way, TI dis p 1 ,p x is also a combination of direct impact.…”

Section: A Direct Inter-frame Dependencymentioning

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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“…Moreover, using the NEA to encrypt the video with high resolutions can result in high computational complexity, which makes it impossible to meet the requirements of real-time transmission [23]. Therefore, selective encryption (SE) algorithms [24][25][26][27][28] for video have been attracting much attention.…”

Section: Related Workmentioning

confidence: 99%

A multi-level approach with visual information for encrypted H.265/HEVC videos

Wen¹,

Tu²,

Zhang³

et al. 2020

Preprint

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High-efficiency video coding (HEVC) encryption has been proposed to encrypt syntax elements for the purpose of video encryption. To achieve high video security, to the best of our knowledge, almost all of the existing HEVC encryption algorithms mainly encrypt the whole video, such that the user without permissions cannot obtain any viewable information. However, these encryption algorithms cannot meet the needs of customers who need part of the information but not the full information in the video. In many cases, such as professional paid videos or video meetings, users would like to observe some visible information in the encrypted video of the original video to satisfy their requirements in daily life. Aiming at this demand, this paper proposes a multi-level encryption scheme that is composed of lightweight encryption, medium encryption and heavyweight encryption, where each encryption level can obtain a different amount of visual information. First, we use AES-CTR to generate a pseudo-random number sequence. Then, the main syntax elements in the H.265/HEVC encoding process are encrypted by a pseudo-random sequence. In the lightweight encryption level, the syntax element of the luma intraprediction model is chosen for encryption. In the medium encryption level, the syntax element of the DCT coefficient sign is employed for scrambling encryption. In the heavyweight encryption level, syntax elements of both the luma intraprediction model and the DCT coefficient sign are encrypted simultaneously by the pseudo-random sequence. It is found that both encrypting the luma intraprediction model (IPM) and scrambling the syntax element of the DCT coefficient sign can achieve the performance of a distorted video in which there is still residual visual information, while encrypting both of them can implement the intensity of encryption and one cannot gain any visual information. The experimental results meet our expectations appropriately, indicating that there is a different amount of visual information in each encryption level. Meanwhile, users can flexibly choose the encryption level according to their various requirements.

show abstract

An efficient Lagrangian multiplier selection method based on temporal dependency for rate–distortion optimization in H.265/HEVC

Cited by 12 publications

References 21 publications

GOP Structure-Independent Quantization Parameter Cascading in Video Coding

GOP Structure-Independent Quantization Parameter Cascading in Video Coding

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

A multi-level approach with visual information for encrypted H.265/HEVC videos

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