Optimal Lagrange multipliers for dependent rate allocation in video coding

Abreu, António; Cheung, Gene; Frossard, Pascal; Pereira, Fernando

doi:10.1016/j.image.2018.02.003

Cited by 11 publications

(6 citation statements)

References 32 publications

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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%

“…There are also some studies in which inter-frame dependency is not directly quantified but implied when solving optimal QP or λ. In [16], a dynamic programming based approach was proposed to search for the optimal λ, which showed considerable coding performance. Yang et al [17]- [19] related distortion and bits of L0 with distortion and bits of other layers, and then solved the optimal QP for other layers based on QP of L0.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: A Direct Inter-frame Dependencymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Wei

Zhou

et al. 2020

IEEE Access

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“…where Lagrangian multiplier λ is chosen so that the optimal solution x to (9) has rate R(x) ≤ R max . [36,37] discussed how to select an appropriate λ. We focus on how ( 9) is solved for a given λ > 0.…”

Section: Rate-constrained Maximum a Posteriori (Map) Problemmentioning

confidence: 99%

Joint Denoising/Compression of Image Contours via Shape Prior and Context Tree

Zheng¹,

Cheung

Florêncio

2018

IEEE Trans. on Image Process.

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The advent of depth sensing technologies means that the extraction of object contours in images-a common and important pre-processing step for later higher level computer vision tasks like object detection and human action recognition-has become easier. However, captured depth images contain acquisition noise and the detected contours suffer from errors as a result. In this paper, we propose to jointly denoise and compress detected contours in an image for bandwidth-constrained transmission to a client, who can then carry out aforementioned application-specific tasks using the decoded contours as input. First, we prove theoretically that in general a joint denoising/compression approach can outperform a separate two-stage approach that first denoises then encodes contours lossily. Adopting a joint approach, we propose a burst error model that models typical errors encountered in an observed string of directional edges. We then formulate a rate-constrained maximum a posteriori problem that trades off the posterior probability of an estimated string given with its code rate. We design a dynamic programming algorithm that solves the posed problem optimally, and propose a compact context representation called total suffix tree that can reduce complexity of the algorithm dramatically. To the best of our knowledge, we are the first in the literature to study the problem of joint denoising/compression of image contours and offer a computation-efficient optimization algorithm. Experimental results show that our joint denoising/compression scheme can reduce bitrate by up to 18% compared with a competing separate scheme at comparable visual quality.

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“…It is well-known that when λ sweeps from zero to infinity, the solution to ( 6) traces out the convex hull of the rate distortion curve, which is a nonincreasing function. Hence, the bisection method in [12] can be used to find the optimal λ. Therefore, the task at hand is to find the optimal solution to the problem expressed in (6).…”

Section: Coding Optimization Of Occlusion-inducing Depth Pixelsmentioning

confidence: 99%

Optimization of Occlusion-Inducing Depth Pixels in 3-D Video Coding

Gao

Özçinar

Smolić

2018

2018 25th IEEE International Conference on Image Processing (ICIP)

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The optimization of occlusion-inducing depth pixels in depth map coding has received little attention in the literature, since their associated texture pixels are occluded in the synthesized view and their effect on the synthesized view is considered negligible. However, the occlusion-inducing depth pixels still need to consume the bits to be transmitted, and will induce geometry distortion that inherently exists in the synthesized view. In this paper, we propose an efficient depth map coding scheme specifically for the occlusion-inducing depth pixels by using allowable depth distortions. Firstly, we formulate a problem of minimizing the overall geometry distortion in the occlusion subject to the bit rate constraint, for which the depth distortion is properly adjusted within the set of allowable depth distortions that introduce the same disparity error as the initial depth distortion. Then, we propose a dynamic programming solution to find the optimal depth distortion vector for the occlusion. The proposed algorithm can improve the coding efficiency without alteration of the occlusion order. Simulation results confirm the performance improvement compared to other existing algorithms.

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Optimal Lagrange multipliers for dependent rate allocation in video coding

Cited by 11 publications

References 32 publications

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

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

Joint Denoising/Compression of Image Contours via Shape Prior and Context Tree

Optimization of Occlusion-Inducing Depth Pixels in 3-D Video Coding

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