Coding Unit Depth Research Articles

Spatio-temporal correlation-based fast coding unit depth decision for high efficiency video coding

The exhaustive block partition search process in high efficiency video coding (HEVC) imposes a very high computational complexity on test module of HEVC encoder (HM). A fast coding unit (CU) depth algorithm using the spatio-temporal correlation of the depth information to fasten the search process is proposed. The depth of the coding tree unit (CTU) is predicted first by using the depth information of the spatio-temporal neighbor CTUs. Then, the depth information of the adjacent CU is incorporated to skip some specific depths when encoding the sub-CTU. As compared with the original HM encoder, experimental results show that the proposed algorithm can save more than 20% encoding time on average for intra-only, low-delay, low-delay P slices, and random access cases with almost the same rate-distortion performance.

Fast transcoding from H.264 to HEVC based on region feature analysis

The new video coding standard, High Efficiency Video Coding (HEVC), achieves much higher coding efficiency than the state-of-the-art H.264. Transcoding H.264 video to HEVC video is important to enable gradual migration to HEVC. Therefore, a fast H.264 to HEVC transcoding algorithm based on region feature analysis is proposed. First, each frame is segmented into three regions in units of coding tree unit (CTU) based on the correlation between image coding complexities and coding bits of the H.264 source stream. Then the searching depth range of each CTU is adaptively decided according to the region type. After that, motion vectors are de-noise filtered and clustered in order to analyze the region features of coding unit (CU). Based on the analysis results, the minimum searching depth of CU and partitions of prediction unit (PU) are optimally selected, and the motion vector predictor and search window size of motion estimation are also optimally decided for further reduction of the computational complexity. Experimental results show that the proposed algorithm achieves a significant improvement on transcoding speed, while maintaining high Rate-Distortion performance.

Fast CU Splitting and Pruning for Suboptimal CU Partitioning in HEVC Intra Coding

High Efficiency Video Coding (HEVC), a new video coding standard currently being established, adopts a quadtree-based Coding Unit (CU) block partitioning structure that is flexible in adapting various texture characteristics of images. However, this causes a dramatic increase in computational complexity compared to previous video coding standards due to the necessity of finding the best CU partitions. In this paper, a fast CU splitting and pruning method is presented for HEVC intra coding, which allows for significant reduction in computational complexity with small degradations in rate-distortion (RD) performance. The proposed fast splitting and pruning method is performed in two complementary steps: 1) early CU split decision and 2) early CU pruning decision. For CU blocks, the early CU splitting and pruning tests are performed at each CU depth level according to a Bayes decision rule method based on low-complexity RD costs and full RD costs, respectively. The statistical parameters for the early CU split and pruning tests are periodically updated on the fly for each CU depth level to cope with varying signal characteristics. Experimental results show that our proposed fast CU splitting and pruning method reduces the computational complexity of the current HM to about 50% in encoding time with only 0.6% increases in BD rate.

Fast Enhancement Layer Encoding Method using CU Depth Correlation between Adjacent Layers for SHVC

This paper proposes a fast enhancement layer coding method to reduce computational complexity for Scalable HEVC (SHVC) which is based on High Efficiency Video Coding (HEVC). The proposed methoddecreases encoding time by simplifying Rate Distortion Optimization (RDO) for enhancement layers (EL). The simplification is achieved by restricting CU depths based on the correlation of coding unit (CU) depths between adjacent layers and scalability (spatial or quality) of EL. Comparing with the performance of SHM 1.0 software encoder, the proposed method reduces the encoding time by up to 31.5%.

Fast CU size decision and mode decision algorithm for HEVC intra coding

The emerging international standard of High Efficiency Video Coding (HEVC) is a successor to H.264/AVC. In the joint model of HEVC, the tree structured coding unit (CU) is adopted, which allows recursive splitting into four equally sized blocks. At each depth level, it enables up to 34 intra prediction modes. The intra mode decision process in HEVC is performed using all the possible depth levels and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency but requires a very high computational complexity. In this paper, we propose a fast CU size decision and mode decision algorithm for HEVC intra coding. Since the optimal CU depth level is highly content-dependent, it is not efficient to use a fixed CU depth range for a whole image. Therefore, we can skip some specific depth levels rarely used in spatially nearby CUs. Meanwhile, there are RD cost and prediction mode correlations among different depth levels or spatially nearby CUs. By fully exploiting these correlations, we can skip some prediction modes which are rarely used in the parent CUs in the upper depth levels or spatially nearby CUs. Experimental results demonstrate that the proposed algorithm can save 21% computational complexity on average with negligible loss of coding efficiency.

An Effective CU Size Decision Method for HEVC Encoders

The emerging high efficiency video coding standard (HEVC) adopts the quadtree-structured coding unit (CU). Each CU allows recursive splitting into four equal sub-CUs. At each depth level (CU size), the test model of HEVC (HM) performs motion estimation (ME) with different sizes including 2N × 2N, 2N × N, N × 2N and N × N. ME process in HM is performed using all the possible depth levels and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency but requires a very high computational complexity. In this paper, we propose a fast CU size decision algorithm for HM. Since the optimal depth level is highly content-dependent, it is not efficient to use all levels. We can determine CU depth range (including the minimum depth level and the maximum depth level) and skip some specific depth levels rarely used in the previous frame and neighboring CUs. Besides, the proposed algorithm also introduces early termination methods based on motion homogeneity checking, RD cost checking and SKIP mode checking to skip ME on unnecessary CU sizes. Experimental results demonstrate that the proposed algorithm can significantly reduce computational complexity while maintaining almost the same RD performance as the original HEVC encoder.

계층 간 CU 깊이 예측을 이용한 HEVC SVC 고속 부호화 방법

In this paper, we propose a fast mode decision method that determines the coding unit depth for enhancement layers to improve an encoding speed of a scalable video encoder based on HEVC. To decide the coding unit depth of the enhancement layer, firstly, the coding unit depth of the corresponded coding unit in the basement layer is employed. At this stage, the final CU depth is decided by calculating the rate-distortion costs of one lower depth to one upper depth of the referenced depth. The proposed method can reduce a computational load since it does not calculate the rate-distortion costs for all the depths of a target CU. We found that the proposed algorithm decreases encoding complexity of 26% with approximately 1.4% bit increment, compared with the simulcast encoder of the HM 4.0.

Fast encoding algorithm based on depth of coding-unit for high efficiency video coding

In high efficiency video coding (HEVC) scheme, the split structure of the largest coding-unit (LCU) is highly variable and laborious due to its recursive quad-tree representation. Thus, the computational complexity of the HEVC encoder increases dramatically. A fast HEVC encoding method is proposed to predict the split structure of the current LCU by using the same structure of the co-located LCU in the reference or temporally-previous frame, in order to reduce the encoding computational complexity. Simulation results show that the proposed method can achieve a reduction in encoding time of 21.3% on average, with a negligible average PSNR loss and a negligible bit rate increase compared with the original HEVC encoding scheme.

Complexity control of high efficiency video encoders for power-constrained devices

The emerging High Efficiency Video Coding (HEVC) standard is expected to require much more processing power than its predecessors due to the higher algorithmic complexity of new coding tools and associated data structures. This paper proposes a novel complexity control method for the near future HEVC encoders running on power-constrained devices. The proposed method is based on a decision algorithm that dynamically adjusts the depth of the Coding Units (CU) defined by quad-tree structures. New evidence about the relationship between CU depth and coding complexity is used to selectively constrain the CU depth in order to not exceed a predefined complexity target. The experimental results show that the encoder computational complexity can be downscaled by up to 60% at the cost of negligible loss of rate-distortion (RD) performance. The proposed method finds application in the near future multimedia portable devices using HEVC codecs.