CART-based fast CU size decision and mode decision algorithm for 3D-HEVC

Jing, Ruihai; Zhang, Qian; Wang, Bin; Cui, PengTao; Yan, Tao; Huang, Jingcao

doi:10.1007/s11760-018-1347-0

Cited by 13 publications

(5 citation statements)

References 17 publications

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“…Fast depth intra coding algorithms I C h e n [ 12], Fu [13], Saldanha [14], Chen [15] II Shen [16], Hamout [17], Zhang [18], Lei [19], Guo [20] Zhao [21], Sanchez [22]- [23], Park [24], Zhang [25] III Li [26], Peng [27], Jing [28] is listed in Table 1. The type I is to reduce the number of unnecessary traversal coding units (CUs) or terminate CU partitioning early, the type II is to reduce the prediction modes or optimise DMMs, and the type III is a comprehensive algorithm including the first two types.…”

Section: Typementioning

confidence: 99%

“…Peng et al [27] set a certain threshold of the minimum RDcost to reduce candidate modes, and using the properties of the current CU to skip smaller CU size. Jing et al [28] proposed a classification and regression tree to predict the depth layer and reduce intra prediction modes.…”

Section: Typementioning

confidence: 99%

“…Jing et al. [28] proposed a classification and regression tree to predict the depth layer and reduce intra prediction modes.…”

Section: Introductionmentioning

confidence: 99%

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Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC

Wang

et al. 2020

IET Image Processing

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To alleviate the computation burden of the depth intra coding in 3D‐HEVC, a complexity reduction scheme based on texture feature and spatio‐temporal correlation is proposed. Firstly, a maximum splitting depth layer decision algorithm is proposed to reduce unnecessary splitting depth layer of the coding tree unit utilising the information of the previous encoded I frame in the same view. Secondly, a new texture complexity model is built by pixel‐based statistical method combined with edge detection. Based on the proposed model, the coding unit block is divided into the smooth block, texture or edge block. On the coding unit level, an early termination of coding unit splitting algorithm for smooth blocks is proposed to filter out unnecessary coding blocks. Thirdly, on the predicting unit level, a fast candidate mode decision algorithm considering predicting unit's types and spatial correlation is proposed to decide the candidate mode list directly. Experimental results describe that the proposed algorithm reduces 53.8% depth intra coding time on average, with 0.43% BD‐rate loss on synthesised views.

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Section: Typementioning

confidence: 99%

Section: Typementioning

confidence: 99%

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Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC

Wang

et al. 2020

IET Image Processing

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“…To extend HEVC to 3D video, Joint Collaborative Team on 3D Video Coding Extensions (JCT-3V) was jointly formed by the ITU-T Visual Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). The JCT-3V produced two extensions of HEVC: multiview video HEVC (MV-HEVC) [23,24] and 3D extension of HEVC (3D-HEVC) [25,26]. The latter is the current state-of-the-art encoder for MVD data, which jointly encodes the texture and depth videos for increased coding efficiency.…”

Section: Introductionmentioning

confidence: 99%

No-reference quality metric for HEVC compression distortion estimation in depth maps

Farid

Lucenteforte

Grangetto

2019

SIViP

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Multiview video plus depth (MVD) is the most popular 3D video format due to its efficient compression and provision for novel view generation enabling the freeviewpoint applications. In addition to color images, MVD format provides depth maps which are exploited to generate intermediate virtual views using the depth image based rendering (DIBR) techniques. Compression affects the quality of the depth maps which in turn may introduce various structural and textural distortions in the DIBR synthesized images. Estimation of the compression related distortion in depth maps is very important for a high quality 3D experience. The task becomes challenging when the corresponding reference depth maps are unavailable e.g., when evaluating the quality on the decoder side. In this paper, we present a no-reference quality assessment algorithm to estimate the distortion in the depth maps induced by compression. The proposed algorithm exploits the depth saliency and local statistical characteristics of the depth maps to predict the compression distortion. The proposed 'depth distortion evaluator' (DDE) is evaluated on depth videos from standard MVD database compressed with the state-of-the-art high efficiency video coding (HEVC) at various quality levels. The results demonstrate that DDE can be used to effectively estimate the compression distortion in depth videos.

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“…This problem is even worse when encoding a 3D video, requiring to process several views in parallel, rising the encoding effort due to the extra tools used for depth map coding [17]. Some works proposed depth map time-saving techniques for single-core systems [18][19][20][21][22][23]; however, their speedup gains do not allow real-time 3D video encoding. Our early works explored depth modeling mode one (DMM-1) parallelism under multicore [24] and GPU [25] architectures.…”

Section: Introductionmentioning

confidence: 99%

Analysis of parallel encoding using tiles in 3D High Efficiency Video Coding

Sanchez

Saldanha

Agostini

et al. 2019

SIViP

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This paper analyzes the usage of tiles in 3D-High Efficiency Video Coding. We investigate the encoding impact of some tiles divisions using a Bjontegaard delta rate (BD-rate) on the common test conditions for 3D videos. This analysis demonstrated dividing the video into square tiles increases the encoding performance compared to non-square tiles (about 2.2%). In another analysis, we concluded the workload is highly unbalanced in the uniform distribution contributing to limit the speedup possibilities for the homogeneous multicore systems. Authors are not aware of any work focusing on balancing depth maps workload in tiles; therefore, we pointed out relevant studies and solutions for future projects in this open research area.

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CART-based fast CU size decision and mode decision algorithm for 3D-HEVC

Cited by 13 publications

References 17 publications

Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC

Fast depth intra coding based on texture feature and spatio‐temporal correlation in 3D‐HEVC

No-reference quality metric for HEVC compression distortion estimation in depth maps

Analysis of parallel encoding using tiles in 3D High Efficiency Video Coding

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