Gradient-based fast decision for intra prediction in HEVC

Zhang, Yongfei; Li, Zhe; Li, Bo

doi:10.1109/vcip.2012.6410739

Cited by 66 publications

(29 citation statements)

References 4 publications

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“…A homogeneous region is likely Fig. 3 Proportions of depths for different class sequences to utilize a larger CU size or low-level CUs, and a complex region will be split into smaller CUs with a high probability [7], [8]. An example of this is illustrated in Fig.…”

Section: Proposed Algorithmmentioning

confidence: 99%

Edge Detector Based Fast Level Decision Algorithm for Intra Prediction of HEVC

Shi

Jiang

Song

et al. 2015

Journal of Signal Processing

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High efficiency video coding (HEVC) achieves significant higher coding efficiency than previous video coding standards. In the intra prediction of HEVC, prediction unit sizes from 4×4 to 64×64 are employed, respectively defined as levels 1 to 5, to achieve higher coding efficiency. Nevertheless, this is at the expense of high computational complexity. This paper proposes a fast algorithm for the intra prediction of HEVC, which can efficiently decide the level on the basis of the roberts-cross edge detector. The proposed algortihm utilizes the high correlation between regional texture and prediction unit partitioning. It is mainly composed of a bottom-up level decision method and an efficient decision flow based on an authentic image feature. Furthermore, chrominance information is also employed to decide the prediction unit partitioning. The experimental results for the proposed algorithm demonstrated that it achieved a task with greatly reduced computational complexity compared with the original HEVC. The average time-saving is approximately 37%, while the increase in bit rate and decrease in PSNR are negligible.

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Section: Proposed Algorithmmentioning

confidence: 99%

Edge Detector Based Fast Level Decision Algorithm for Intra Prediction of HEVC

Shi

Jiang

Song

et al. 2015

Journal of Signal Processing

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“…There is a clear tendency to split less homogeneous areas into smaller blocks while keeping homogeneous regions in large blocks. Proposed methods in [8] and [9] estimate texture complexity using gradient information. In [8], horizontal and vertical Sobel kernels are used to calculate gradient information and partition decision is taken based on standard deviations of gradient values.…”

Section: Related Workmentioning

confidence: 99%

“…This is achieved by comparing the sum of RD costs of constituent blocks with the cost of coding unit. In [9], texture complexity calculated from directional gradients are compared with an adaptive threshold based on quantization parameter (QP) and prediction unit (PU) size and less complex CUs are merged together to generate the final partition structure. A content adaptive threshold determination mechanism has been proposed in [10], which reports a 28.8% time saving for HD videos.…”

Section: Related Workmentioning

confidence: 99%

“…Homogeneous regions of an image segment can be identified by performing a texture analysis on the region of interest. In the methods proposed in [8] and [9], gradient information of the coding unit image segment has been utilized to derive texture complexity. However, a texture analysis method, which is less computationally expensive and which could be used as a measure of homogeneity is required to make an analysis of the coding unit under consideration.…”

Section: Proposed Algorithmmentioning

confidence: 99%

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Efficient coding unit size selection based on texture analysis for HEVC intra prediction

Mallikarachchi

Fernando

Arachchi

2014

2014 IEEE International Conference on Multimedia and Expo (ICME)

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Determining the best partitioning structure for a given Coding Tree Unit (CTU) is one of the most time consuming operations within the HEVC encoder. The brute force search through quadtree hierarchy has a significant impact on the encoding time of high definition (HD) videos. This paper presents a fast coding unit size decision-taking algorithm for intra prediction in HEVC. The proposed algorithm utilizes a low complex texture analysis technique based on the local range property of a pixel in a given neighborhood. Simulation results show that the proposed algorithm achieves an average of 72.24% encoding time efficiency improvement with similar rate distortion performance compared to HEVC reference software HM12.0 for HD videos.

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“…In the HEVC Test Model (HM), which is the standard implementation of HEVC, all CU divisions from depth 0 to depth 3 require RD to be computed, resulting in a large number of calculations and a significant complexity for HEVC. To reduce such complexity several algorithms have been proposed that target the reduction of RD calculation and CU division [6]- [10]. In this paper, we propose a simple and fast CU division algorithm in which only a few pixels around a CU being processed are analyzed instead of the RD calculation in Eq.…”

Section: Introductionmentioning

confidence: 99%

A Simple and Fast CU Division Algorithm for HEVC Intra Prediction

Wang

Takagi

Yoshitake

2017

IEICE Trans. Inf. & Syst.

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SUMMARYHigh Efficiency Video Coding is a new video coding standard after H.264/AVC. By introducing a flexible coding unit, which can be recursively divided from 64×64 to 8×8 blocks in a Quadtree-Structure, HEVC achieves significantly higher coding efficiency than the previous standards. With the flexible CU structure, HEVC can effectively adapt to highly varying contents with a smaller CU or to flat contents with a larger CU, making it suitable for applications from mobile video to super high definition television. On the other hand, CU division does incur high computational cost for HEVC. In this paper, we propose a simple and fast CU division algorithm by using only a subset of pixels to determine when CU division happens. Experiment results show that our algorithm can achieve prediction quality close to HEVC Test Model with much lower computational cost.

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Gradient-based fast decision for intra prediction in HEVC

Cited by 66 publications

References 4 publications

Edge Detector Based Fast Level Decision Algorithm for Intra Prediction of HEVC

Edge Detector Based Fast Level Decision Algorithm for Intra Prediction of HEVC

Efficient coding unit size selection based on texture analysis for HEVC intra prediction

A Simple and Fast CU Division Algorithm for HEVC Intra Prediction

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