Algorithm For High Efficiency Video Coding Research Articles

Two-Stage Perceptual Quality Oriented Rate Control Algorithm for HEVC

As a practical technique in mainstream video coding applications, rate control dominates important to ensure compression quality with limited bitrates constraints. However, most rate control methods mainly focus on objective quality while ignoring the perceptual quality improvement for human eyes. In this paper, we propose a two-stage rate control algorithm to optimize the perceptual quality at the frame encoding stage and the coding tree unit (CTU) encoding stage for high efficiency video coding (HEVC), respectively. Firstly, for the frame encoding stage, with inter-frame distortion dependency consideration, a frame-level rate control method is presented by adjusting the frame-level Lagrange multiplier adaptively with a preprocessing method. Secondly, for the CTU encoding stage, we propose a saliency-based CTU-level perceptual quality rate control algorithm, which employs CTU-level saliency weight to adjust the perceptual rate-distortion (R-D) model. We conduct the CTU-level rate control by an optimized Lagrange multiplier and quantization parameter (QP) to achieve perceptual quality optimization. Extensive experimental results reveal that, compared with state-of-the-art rate control methods on HEVC, our algorithm achieves significant perceptual coding performance with improved subjective visual quality.

A Novel Coding Scheme for Large-Scale Point Cloud Sequences Based on Clustering and Registration

Due to the huge volume of point cloud data, storing and transmitting it is currently difficult and expensive in autonomous driving. Learning from the high-efficiency video coding (HEVC) framework, we propose a novel compression scheme for large-scale point cloud sequences, in which several techniques have been developed to remove the spatial and temporal redundancy. The proposed strategy consists mainly of three parts: intracoding, intercoding, and residual data coding. For intracoding, inspired by the depth modeling modes (DMMs), in 3-D HEVC (3-D-HEVC), a cluster-based prediction method is proposed to remove the spatial redundancy. For intercoding, a point cloud registration algorithm is utilized to transform two adjacent point clouds into the same coordinate system. By calculating the residual map of their corresponding depth image, the temporal redundancy can be removed. Finally, the residual data are compressed either by lossless or lossy methods. Our approach can deal with multiple types of point cloud data, from simple to more complex. The lossless method can compress the point cloud data to 3.63% of its original size by intracoding and 2.99% by intercoding without distance distortion. Experiments on the KITTI dataset also demonstrate that our method yields better performance compared with recent well-known methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article deals with the problem of efficient compression of point cloud sequences that come from light detection and ranging (LiDARs) mounted on autonomous mobile robots. The vast amount of point cloud data could be an important bottleneck for transmission and storage. Inspired by the HEVC algorithm, we develop a novel coding architecture for the point cloud sequence. The scans are divided into intraframe and interframe, which are encoded separately using different techniques. Our method can be used for the compression of LiDAR point cloud sequences or dense LiDAR point cloud map and will significantly reduce the transmission bandwidth and storage spaces. We have to admit that although our method is less effective for real-time solutions, it can be highly efficient for off-line applications. Future studies will concentrate on further optimizing the coding algorithm to reduce the computational complexity and trying to find a balance between them.

Fast Intra Mode Decision Algorithm for HEVC Based on Block Textural Properties

In order to achieve greater coding efficiency compared with the previous video coding standards, various advanced coding techniques are used in the High Efficiency Video Coding (HEVC) standard, such as a flexible partition and a large number of intra prediction modes. However, these techniques lead to much greater complexity that restricts HEVC from realtime applications. To solve this problem, a fast intra mode decision algorithm is proposed in this paper that uses the block’s textural properties to determine the partition depth range and decide whether to split or skip smaller sizes of the coding unit. Besides that, the number of candidate modes for the rough mode decision process is also reduced depending on the block’s property. Experimental results for the recommended test sequences by the JCT-VC show that the proposed algorithm can save an average of 44% encoder time with a slight loss in performance compared to the reference software HM-16.20.

VLSI Architecture of Block Matching Algorithms for Motion Estimation in High Efficiency Video Coding

High-efficiency video coding (HEVC) is a latest video coding standard and the motion estimation unit is the most important block. The work presents the different types of Matching Criteria for Block-Based Motion Estimation technique in HEVC standard. HEVC requires fast motion estimation algorithms to have better real time performance. The hardware implementation of motion estimation helps to achieve high speed though parallel processing. An improved block matching technique is designed with reduced blocks for HEVC. The proposed method has less execution time where only blocks having motion are compared for prediction computation. The searching time complexity is dependent on the number of blocks that are having motion. The searching time of frame having small motion can be reduced to 80–85% as compared to the traditional full search algorithm. In the paper, sum of absolute difference, mean square error and mean absolute difference are computed to find the best matching algorithm for HEVC. However, SAD has less computational complexity with compare to other matching criteria. The results suggest that proposed motion estimation algorithm has better performance with compare to similar previous work.

A low complexity and computationally scalable fast motion estimation algorithm for HEVC

Motion Estimation (ME) is one of the most computationally demanding parts of video encoders. The Test Zone (TZ) search is a popular fast ME algorithm, which is recommended for High-Efficiency Video Coding (HEVC). While the TZ search achieves an excellent coding efficiency, it is not a favorable choice for hardware implementations due to 1) a relatively high computational complexity, 2) inducing data dependency among the neighboring blocks, which complicates hardware implementations and parallel processing in software implementations, and 3) lack of computational adjustability, which is required for video encoding in power-constrained devices. This paper diagnoses the cause of these issues to be in the multiple starting search points of the TZ search algorithm. Accordingly, a method is proposed to find a single reliable starting point that replaces the first step of the TZ search algorithm. To do so, both current and reference frames are analyzed using a complex wavelet transform, and similar salient points are identified among the two frames. Then a light-weight process is used to match these points to find a single reliable starting point. The reliability of this point leads to reduced zonal refinement range with negligible cost in compression efficiency. Since adjusting the refinement range can be used as an effective way for adjusting the complexity, this results in a computationally scalable ME algorithm, named FMECWT. In contrast to the existing methods, FMECWT does not rely on neighboring blocks, which eliminates the inherent data dependency of TZ search. Experimental results show that FMECWT achieves ~35% to ~85% ME time reduction compared to TZ search, with only 0.1% to 1.7% increase in BD-Rate.

Fast algorithm for HEVC intra‐coding implemented by preprocessing

Compared to previous video compression standards H.264/AVC, high-efficiency video coding (HEVC) introduces a recursive quad-tree structure in intra-coding and adds intra-mode from 9 to 35 to achieve higher coding efficiency. The update significantly improves the performance of intra-coding. However, it greatly increases the amount of computation, and this will increase the need for the fast algorithm and hardware design that can satisfy the real-time encoding of HEVC encoder. In this study, the authors propose a fast intra-coding algorithm based on analysis of original pixel gradient texture. The algorithm consists of two steps, fast coding unit size decision and reduction of candidate modes. The experimental results show that compared with the HM16.7 encoder, the optimisation algorithm can obtain 50.7% time reduction on average with 1.32% Bjontegaard distortion (BD)-rate increase and 0.07 dB BD-peak-signal-to-noise ratio loss. Meanwhile, this study designs a pre-processing hardware structure based on original pixels. With TSMC 90 nm complementary metal oxide semiconductor technology, the proposed structure can achieve 625 MHz working frequency at the cost of 2094 gates, which can fulfil the throughput requirement of 8K × 4K@46 fps real-time encoding.

A Motion-Based Partitioning Algorithm for HEVC Using a Pre-Analysis Stage

The High Efficiency Video Coding (HEVC) standard has shown large improvements in coding efficiency compared with previous standards. In particular, HEVC outperforms H.264/MPEG-4 Advanced Video Coding by up to 50% in terms of bitrate reduction for similar perceptual quality. This improvement is the result of the introduction of new coding tools, which enable the representation of data using fewer bits, but at the cost of long computation times. One of the most significant tools introduced by HEVC is the novel quadtree-based structure called the coding tree unit (CTU), which can be subsequently split into coding units (CUs), prediction units (PUs), and transform units (TUs), providing huge flexibility in the encoding. However, selecting the optimal tree partitioning requires the evaluation of a huge number of possibilities, which constitutes the most complex operation for the encoder. In order to tackle this task, this paper proposes a CTU/CU partitioning algorithm based on a pre-analysis stage. This stage performs a fast motion estimation that provides preliminary information to the encoder, including estimate distortion costs, which enables the building of the least-cost quadtree. On the basis of this tree, the evaluation performed by the encoder is restricted to a subset of PUs. After a thorough statistical analysis of numerous CU/PU combinations, we propose two different configurations that prioritize each of the target variables: coding efficiency and time reduction. In the former case, 58.09% of the encoding time can be saved at the cost of a 2.51% increase in Bjontegaard delta (BD)-rate, while a larger reduction of 63.08% is achieved with a 3.43% increase in BD-rate in the later case.

Discrete wavelet transform-based fast and high-efficient lossless intraframe compression algorithm for high-efficiency video coding

High-efficiency video coding (HEVC) is a very common application in today’s electronics field. Lossless intraframe compression is preferred for many specific applications. Compared to lossy intracompression or interframe encoding, intraframe encoding has lower computation complexity but an unsatisfactory compressed bit-rate. Extant optimization algorithms center on improving coded bits in space domains and few include considerations for accelerating encoding time. We focus on video compression in the frequency domain to reduce bit-rate while saving encoding time. The proposed method involves placing discrete wavelet transform in front of the traditional HEVC tools to transform a given frame into frequency coefficients. To accelerate the encoding process, fast prediction mode skip and CU depth decision are used to bypass certain unnecessary computations based on texture detection results. The experimental results indicated that our method reduces bit-rate by 6.466% on average with 48.068% encoding time savings compared to the original HEVC encoding.

Homogeneity-based fast CU partitioning algorithm for HEVC intra coding

High Efficiency Video Coding (HEVC) is a new video coding standard released as a successor for H.264/AVC. It expected to reduce by 50% the bitrate for the same perceptual quality. One of the major contributors to the higher compression performance of HEVC is the introduction of larger Coding Units (CU) with recursive partitioning mechanisms. This encoding performance is accompanied by a high computational complexity, which makes it very difficult to achieve real-time encoding especially if we aim to implement this encoder on embedded platforms. In this context, this paper suggests a fast CU partitioning algorithm for Intra-only (All Intra) configuration. The proposal aims to early terminate CU partitioning for homogeneous regions in the video frame, or skip some depths for high textured regions. The decision of Split/Non-split is based on homogeneity classification algorithm, which allows us to avoid the test of the all depths in order to determine the best CU size. Experimental results confirm that the proposed approach can reduce up to 41% of encoding time in average for different video classes and can reach up to 58% for high homogenous texture video sequences.

Hierarchical complexity control algorithm for HEVC based on coding unit depth decision

The next-generation High Efficiency Video Coding (HEVC) standard reduces the bit rate by 44% on average compared to the previous-generation H.264 standard, resulting in higher encoding complexity. To achieve normal video coding in power-constrained devices and minimize the rate distortion degradation, this paper proposes a hierarchical complexity control algorithm for HEVC on the basis of the coding unit depth decision. First, according to the target complexity and the constantly updated reference time, the coding complexity of the group of pictures layer and the frame layer is allocated and controlled. Second, the maximal depth is adaptively assigned to the coding tree unit (CTU) on the basis of the correlation between the residual information and the optimal depth by establishing the complexity-depth model. Then, the coding unit smoothness decision and adaptive low bit threshold decision are proposed to constrain the unnecessary traversal process within the maximal depth assigned by the CTU. Finally, adaptive upper bit threshold decision is used to continue the necessary traversal process at a larger depth than the maximal depth of allocation to guarantee the quality of important coding units. Experimental results show that our algorithm can reduce the encoding time by up to 50%, with notable control precision and limited performance degradation. Compared to state-of-the-art algorithms, the proposed algorithm can achieve higher control accuracy.

All zero block detection for HEVC based on the quantization level of the maximum transform coefficient

Transform/quantization (T/Q) is one of the high complex modules in high efficiency video coding (HEVC). In this paper, all zero block (AZB) detection algorithm for HEVC is proposed to reduce the complexity of T/Q. The proposed AZB detection algorithm is based on the quantization level of the maximum transform coefficient, which is suitable for both uniform quantizer (UQ) and rate-distortion optimized quantizer (RDOQ). Experimental results show that 46% complexity of T/Q for UQ and 42% for RDOQ can be reduced with negligible loss of video quality and compression efficiency, outperforming the state-of-the-art methods.

Fast Bayesian decision based block partitioning algorithm for HEVC

The newly published High Efficiency Video Coding (HEVC) Standard has greatly enhanced the coding performance in comparison to its predecessors. However, HEVC also has high computational complexity, which limits its application. In this paper, we propose a fast Bayesian Decision based Block Partitioning (BDBP) algorithm for HEVC encoder. Firstly, the scene change detection based on average grey difference is used to divide the video sequence into the online learning phase and the fast partitioning phase. Secondly, in the online learning phase, the statistical parameters are extracted from coding units (CUs) in every depth to establish the Gaussian mixture models which are resolved by expectation maximization algorithm; in the fast partitioning phase, the conditional probabilities for CU to decide partitioning and non-partitioning are calculated. Finally, the minimum risk Bayesian decision rule is used to choose the decision with smaller risk, and the decision is regarded as the judgment of the current CU. Experimental results show that the proposed algorithm reduces the computational complexity of HM13.0 to 54.1% in encoding time with 0.92% increase in the BD-Rate and 0.05dB decrease in the BD-PSNR. Moreover, the proposed algorithm also demonstrates better performance over other state-of-the-art work.

A Hardware-Oriented IME Algorithm for HEVC and Its Hardware Implementation

High Efficiency Video Coding (HEVC), the latest video coding standard, aims to provide coding performance that is much superior to that of its predecessor, H.264, especially for high definition video. To fulfill this goal, the inter-prediction unit (PU) partitions of HEVC are more complex, and the search range of motion estimation (ME) is much larger. As a result, ME becomes a bottleneck in the design of the HEVC inter predictor. In response to this challenge, we developed a hardware-oriented integer ME algorithm and the related hardware implementation. Our proposed algorithm led to a decrease in terms of the Bjontegaard Delta rate when compared with the HEVC test model 15.0. The corresponding hardware solution benefitted from 2-D data reuse supported by horizontal and vertical reference SRAMs, on-chip memory reduction supported by $4\times4$ block compression, and a low-power sum of absolute difference (SAD) tree supported by PU-level chip selection. When adopting a $32\times32$ SAD tree, the minimum and maximum required working frequency for 4K $\times2\text{K}$ at 30 frames/s videos was [375, 500] MHz. These results demonstrated that our proposed solution offered desirable improvement in both coding speed and coding performance.

Key-point Detection based Fast CU Decision for HEVC Intra Encoding

As the most recent video coding standard, High Efficiency Video Coding (HEVC) adopts various novel techniques, including a quad-tree based coding unit (CU) structure and additional angular modes used for intra encoding. These new techniques achieve a notable improvement in coding efficiency at the penalty of significant computational complexity increase. Thus, a fast HEVC coding algorithm is highly desirable. In this paper, we propose a fast intra CU decision algorithm for HEVC to reduce the coding complexity, mainly based on a key-point detection. A CU block is considered to have multiple gradients and is early split if corner points are detected inside the block. On the other hand, a CU block without corner points is treated to be terminated when its RD cost is also small according to statistics of the previous frames. The proposed fast algorithm achieves over 62% encoding time reduction with 3.66%, 2.82%, and 2.53% BD-Rate loss for Y, U, and V components, averagely. The experimental results show that the proposed method is efficient to fast decide CU size in HEVC intra coding, even though only static parameters are applied to all test sequences.

Fast intra coding algorithm for HEVC based on depth range prediction and mode reduction

The latest High Efficiency Video Coding (HEVC) standard only requires 50% bitrate of the H.264/AVC at the same video quality. Due to introduction of more advanced coding tools and techniques, its computational complexity rises rapidly. In this paper, we propose a novel fast Intra coding algorithm. Firstly, a novel feature is proposed to measure the complexity of video content based on the analysis of mode information obtained from a previous frame. Then, a model is built based on the relationship between this feature and Coding Tree Unit (CTU) depth range. According to the model, the unnecessary operations of Coding Unit (CU) split are skipped. Secondly, the correlation between CU distribution structure and mode selection is established. For the prediction of unlikely CU, the last few intra modes in candidate list are eliminated before rate-distortion optimization process. Experimental results demonstrate that the proposed algorithm reduces the encoding time by 43.2% with just 0.47% BD-rate increase compared with HEVC test model. Compared with other state-of-art algorithms, the proposed algorithm achieves better trade-off between complexity reduction and RD performance.

Adaptive intra mode decision for HEVC based on texture characteristics and multiple reference lines

The High Efficiency Video Coding (HEVC) standard was designed to achieve significantly improved coding efficiency compared with the widespread use of H.264/AVC standards. This achievement was motivated by the ever-increasing popularity of high-definition and ultra-HD video application. However, this comes at the expense of a significant increase in encoder complexity, especially in intra-frame coding. To enhance the intra coding performance, a set of 35 intra prediction modes is adopted in HEVC. To reduce the complexity of intra prediction while maintaining the coding performance, an adaptive fast mode decision algorithm for HEVC intra coding based on texture characteristics and multiple reference lines is proposed in this paper. First, we take advantage of pixel values deviation (PVD) to obtain dominate texture direction of prediction unit (PU) and predict the texture prediction direction candidate set out of all 35 intra prediction modes based on texture direction with due consideration of texture complexity and PU size. Second, an adaptive multiple reference line-based intra prediction scheme will be utilized with classification strategy to improve coding efficiency. Third, the relation observed between the costs of two candidate modes will be exploited to improve the efficiency of prediction. Experimental results demonstrate that the proposed algorithm saves 20.45% intra encoding time on average without incurring noticeable performance degradation and outperforms the state-of-the-art intra mode decision algorithms by achieving a better RD performance with approximate encoding time saving.

Fast intra coding based on online learning for high efficiency video coding

The state-of-art high efficiency video coding (HEVC) standard attracts much attention as its excellent performances in video compression in recent years. However the inherent coding complexity of HEVC makes it difficult for real-time application. A fast algorithm for HEVC intra coding based on online learning is proposed in this paper. During learning coding, the partition threshold of coding unit (CU) is obtained by learning the random sample set which conforms to Poisson probability distribution. Meanwhile the threshold of rate distortion cost is also obtained by online learning. After that, the acquired thresholds are used for early skip of CU depth or early termination of CU partition in the stage of fast coding. Anchoring the HM16 test model, the proposed algorithm achieves an important improvement of average time-saving 46.02%. In addition, it is also demonstrated that the proposed algorithm gains higher time efficiency when video sequence is encoded with higher compression efficiency.

Fast mode decision algorithm for HEVC intra coding based on texture partition and direction

High efficiency video coding (HEVC) is the newest video coding standard, which employs some advanced coding techniques as compared to the previous standard H.264. The flexible quad-tree partitioning of coding tree unit (CTU) and various candidate modes of prediction unit (PU) significantly promote the video compression efficiency; however, these techniques lead to a great amount of computational loads. In this paper, a fast mode decision algorithm for HEVC intra coding is proposed based on texture partition and direction. It consists of two sub-algorithms: the CTU depth range prediction (CDRP) and the intra-prediction mode selection (IPMS). The CDRP reduces the recursive partition number of coding unit (CU) based on the correlation between the CTU texture partition and the optimum CU partition, and it first calculates the texture partition flags of different-size CUs from bottom to top. Then, it employs these partition flags to predict the depth range of the current CTU and decide whether to terminate the CU partition in advance. In order to reduce the number of candidate PU modes for the Hadamard optimization, the IPMS first uses the three-step selection of the candidate modes. The first step selects the candidate modes based on the correlation between the texture directions and the optimum PU modes. The second step selects the candidate modes by using the best modes among the selected modes in the first step. The third step selects the candidate modes by using the spatial correlation of the optimum modes between the current PU and its adjacent PUs. Then, in order to reduce the number of candidate modes for the rate-distortion optimization, the IPMS utilizes the numerical relationship of the sorted Hadamard costs of above selected modes, the optimum modes of adjacent PUs and the statistical characteristics of the small-size PUs. Compared to the original algorithm in HEVC test model, the proposed overall algorithm can reduce 60% encoding time on average with only a 1.45% increase in Bjontegaard delta bit rate under the all-intra configuration. Compared to the most of state-of-the-art algorithms, the proposed overall algorithm has better computational performances and similar rate-distortion performances.

Computationally Efficient Motion Estimation Algorithm for HEVC

In this paper, we present a novel computationally efficient motion estimation (ME) algorithm for high-efficiency video coding (HEVC). The proposed algorithm searches in the hexagonal pattern with a fixed number of search points at each grid. It utilizes the correlation between contiguous pixels within the frame. In order to reduce the computational complexity, the proposed algorithm utilizes pixel truncation, adaptive search range, sub-sampling and avoids some of the asymmetrical prediction unit techniques. Simulation results are obtained by using the reference software HM (e n c o d e r_l o w d e l a y_P_m a i n and e n c o d e r_r a n d o m a c c e s s_m a i n profile) and shows 55.49% improvement on search points with approximately the same PSNR and around 1% increment in bit rate as compared to the Test Zonal Search (TZS) ME algorithm. By utilizing the proposed algorithm, the BD-PSNR loss for the video sequences like B a s k e t b a l l P a s s_416 × 240@50 and J o h n n y_1280 × 720@60 is 0.0804 dB and 0.0392 dB respectively as compared to the HM reference software with the e n c o d e r_l o w d e l a y_P_m a i n profile.

A hardware-oriented concurrent TZ search algorithm for High-Efficiency Video Coding

High-Efficiency Video Coding (HEVC) is the latest video coding standard, in which the compression performance is double that of its predecessor, the H.264/AVC standard, while the video quality remains unchanged. In HEVC, the test zone (TZ) search algorithm is widely used for integer motion estimation because it effectively searches the good-quality motion vector with a relatively small amount of computation. However, the complex computation structure of the TZ search algorithm makes it difficult to implement it in the hardware. This paper proposes a new integer motion estimation algorithm which is designed for hardware execution by modifying the conventional TZ search to allow parallel motion estimations of all prediction unit (PU) partitions. The algorithm consists of the three phases of zonal, raster, and refinement searches. At the beginning of each phase, the algorithm obtains the search points required by the original TZ search for all PU partitions in a coding unit (CU). Then, all redundant search points are removed prior to the estimation of the motion costs, and the best search points are then selected for all PUs. Compared to the conventional TZ search algorithm, experimental results show that the proposed algorithm significantly decreases the Bjøntegaard Delta bitrate (BD-BR) by 0.84%, and it also reduces the computational complexity by 54.54%.