A reduced computational effort mode-level scheme for 3D-HEVC depth maps intra-frame prediction

Sanchez, Gustavo; Agostini, Luciano; Marcon, César

doi:10.1016/j.jvcir.2018.05.003

Cited by 13 publications

(12 citation statements)

References 18 publications

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“…The coding efficiency and the time-consuming performance of the proposed algorithm compared with the state-of-the-art fast depth intra coding algorithms for 3D-HEVC [17] and [18] are listed in Table VI. It can be seen that the proposed can achieve more 17.9% and 7.4% of timesaving, respectively, with almost the same average BD-rate results, which indicates the outperformance of the proposed fast algorithm foe 3D-HEVC.…”

Section: B Comparison With the State-of-art Fast 3d-hevc Algorithmsmentioning

confidence: 99%

“…Then, a block-level fast algorithm is proposed, when Skip and DIS modes have a high chance of being selected, avoiding the remaining best mode searching procedure. Reference [18] propose a model-level scheme for reducing the most timeconsuming steps at the intra prediction, with DMM-1 fast pattern selector (DFPS), pattern and gradient-based mode one Filter (P&GMOF) and enhanced depth rough mode decision (ED-RMD) algorithms, the time consuming of depth map intra prediction is saved. In summary, these fast algorithms can be summarized into two sorts, one is to skip some unnecessary modes checking, the other one is to terminate the CU partitioning process earlier.…”

Section: Introductionmentioning

confidence: 99%

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Bi-Layer Texture Discriminant Fast Depth Intra Coding for 3D-HEVC

et al. 2019

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3D-HEVC explores several new intra-frame depth coding tools to improve the coding efficiency, but at the price of high computational complexity, which hinders the practical applications of 3D-HEVC. Therefore, a bi-layer texture discriminant fast depth intra coding for 3D-HEVC is proposed in this paper. With a sum of gradient matrix (SGM), the texture complexity (TC) of current depth coding unit (CU) and its subblocks are calculated at once. The values of TCs indicate whether to split the depth CU further and skip unnecessary DMMs checking. The experimental results show that compared with the original 3D-HEVC, the proposed algorithm reduces the depth encoding time by 44.8%, and the average bit rate of the synthetic viewpoint is only increased by 0.38%, which outperforms the state-of-the-art fast 3D-HEVC algorithms.INDEX TERMS Depth intra coding, 3D-HEVC, CU size decision, fast mode decision.

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Section: B Comparison With the State-of-art Fast 3d-hevc Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bi-Layer Texture Discriminant Fast Depth Intra Coding for 3D-HEVC

et al. 2019

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“…Fu's [13] achieved 50.1% encoding time saving with 0.64% BD‐rate loss. Compared with the [13, 22 25], the proposed overall algorithm has reduced large the encoding time, while maintaining the same visual quality as the encoder. Therefore, it can be observed that the proposed algorithm achieves better coding performance than the other three algorithms in terms of the coding efficiency and the encoding complexity.…”

Section: Resultsmentioning

confidence: 99%

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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“…The proposed decision tree based algorithm for depth intra coding has been implemented in HTM-16.1 [18]. The original depth intra mode decision in HTM-16.1 is an anchor for comparison with the state-of-the-art algorithms [4], [7], [8], [11], [13], [14] and the proposed algorithm. The quantization parameters (QP) were set as 25, 30, 35, and 40 for texture views and 34, 39, 42, and 45 for the corresponding depth views.…”

Section: Simulation Resultsmentioning

confidence: 99%

Fast Depth Intra Coding Based on Decision Tree in 3D-HEVC

Chen

Chan

et al. 2019

IEEE Access

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The coding units (CU) partitioning in the 3D extension of the high efficiency video coding standard (3D-HEVC) is recursively conducted on different block sizes from 64 × 64 to 8 × 8. Besides, the depth coding in 3D-HEVC introduces several new coding tools for each CU to improve the coding efficiency, however, with great computational complexity. It is noted that only a small number of the CUs in recursive partitioning are encoded into the final bitstream. Among these CUs, the CUs with Intra 2N × 2N or Intra N × N as optimal modes have a very small proportion. In this paper, we thus propose an early determination of depth intra coding, where the coding stage of Intra 2N × 2N, Intra N × N or CU Splitting for the CUs could be early skipped based on several Decision Trees. Simulation results show that, with restrict the results from the tree leaves by different Gini thresholds, the proposed algorithm could save 41.14%-71.63% of the depth coding time with only a slight increase in BDBR. INDEX TERMS 3D-HEVC, CU size decision, decision tree, Gini thresholds, depth intra coding, fast mode decision.

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A reduced computational effort mode-level scheme for 3D-HEVC depth maps intra-frame prediction

Cited by 13 publications

References 18 publications

Bi-Layer Texture Discriminant Fast Depth Intra Coding for 3D-HEVC

Bi-Layer Texture Discriminant Fast Depth Intra Coding for 3D-HEVC

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

Fast Depth Intra Coding Based on Decision Tree in 3D-HEVC

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