Jong-Hyeok Lee

Fast coding algorithm based on adaptive coding depth range selection for HEVC

The JCT-VC is developing the next-generation video coding standard, called high efficiency video coding (HEVC). In HEVC, there are three units in a block structure. These units are a coding unit (CU), a prediction unit (PU), and a transform unit (TU). The CU is the basic unit for region splitting (like a macroblock). The CU performs recursive splitting into four blocks of equal size, starting from the treeblock. We use mode information of the current CU to avoid unnecessary CU splitting. To reduce the computational complexity, we propose a depth range selection mechanism (DRSM) using a selecting adaptive depth range. This depth range selection mechanism allows for effective splitting by only processing CUs that need this process. Experimental results show that the proposed algorithm achieves an approximate 48% reduction in encoding time for Random Access HE, compared to the HEVC test model (HM) 6.0 encoder with a BD-bitrate loss of 1.2%.

Novel fast PU decision algorithm for the HEVC video standard

In this paper, we propose a fast PU decision method to reduce encoder complexity. We use an early PU decision in each CU-level based on spatio-temporal analyses and depth correlations. We also consider a classification of motion activity. Experimental results show that the encoding complexity can be reduced by up to 37.98% on average in the random access Main profile configuration with only a small bit-rate increment and a PSNR decrement, compared to high efficiency video coding test model (HM) 7.0 reference software.

Zoom Motion Estimation Using Block-Based Fast Local Area Scaling

Block-based motion estimation (ME) has been widely used in various video coding standards due to its effectiveness in removing temporal redundancy. However, this traditional ME technique suffers the limitation that it can only compensate for a pure parallel translation between frames. Various algorithms have been proposed for estimating other motion models, such as zooming, rotating, tilting, and warping. In spite of good performance for these algorithms, they are not used in the current industrial world because of their high computational complexity and incompatibility with current block-based video coding standards that limit their practical usage. In this paper, we present a novel zoom motion estimation (ZME) and motion compensation algorithm using the local area scaling technique. To represent and encode the zoom motion, we introduce a zoom vector (ZV) that either increases or decreases a reference block size. The resized reference block is then interpolated to the size of the current block in order to perform block matching. For fast ZME, we have also designed a 3-D diamond pattern search to reduce the number of unnecessary search points for the ZV. We have integrated the proposed algorithm into H.264/AVC JM reference software. Experimental results show that an average bit-rate savings of 11.01% (up to 16.87%) can be achieved for high-definition size sequences with an average 0.20 dB gain in peak signal-to-noise ratio and a less than 10% time increment in the hierarchical B structure.

Fast encoding algorithm for high-efficiency video coding (HEVC) system based on spatio-temporal correlation

AbstractVideo compression technology is an importa nt research part to the intelligent user interface for interactive multimedia system using technologies and services such as image processing, pattern recognition, computer vision and cloud computing service. Recently, high-efficiency video coding (HEVC) has been established as the demand of very high-quality multimedia service like ultrahigh definition video service. High-efficiency video coding (HEVC) standard has three units such as coding unit (CU), prediction unit (PU) and transform unit. It has too many complexities to improve coding performance. We propose a fast algorithm which can be possible to apply for both CU and PU parts. To reduce the computational complexity, we propose CU splitting algorithm based on rate–distortion cost of CU about the parent and current levels to terminate the CU decision early. In terms of PU, we develop fast PU decision based on spatio-temporal and depth correlation for PU level. Finally, experimental results show that our algorithm provides a significant time reduction for encoding with a small loss in video quality, compared to the original HEVC Test Model (HM) version 10.0 software and the previous algorithm.

Fast algorithm for the High Efficiency Video Coding (HEVC) encoder using texture analysis

High Efficiency Video Coding (HEVC) is the newest video coding standard for improvement in video data compression. However, the important challenge of the encoding complexity of HEVC is addressed in a new way. For a natural video sequence, a large number of coding blocks are generally skipped in nature. These need not be transmitted and can be generated in the decoder side using reference pictures. An early skip detection technique for HEVC is proposed based on identification of motionless and homogeneous texture-based regions in a video sequence. Entropy is considered as a feature for analysis of coding unit (CU) texture. An entropy difference between coding units is calculated for identification of motionless and homogeneous regions in a video sequence. Complex texture-based regions are generally encoded as asymmetric motion partitioning (AMP) processing units. An early non-AMP detection technique is also proposed for non-skipped coding blocks using the entropy value of a coding unit. The proposed technique achieved a 40% encoding time reduction, compared with the conventional HEVC encoder, with a negligible degradation in video quality.

Fast intra mode decision algorithm based on local binary patterns in High Efficiency Video Coding (HEVC)

A fast intra-mode decision algorithm for High Efficiency Video Coding Range Extension (HEVC RExt) is presented. In the HEVC RExt encoder, the encoding performance of intra-coding is better than the previous HEVC still image encoding standard. In order to use textural information of the most probable mode for intra-prediction, the probability distribution of local binary patterns is analyzed. An intra-mode decision method is proposed based on use of the local binary pattern in the texture of an encoded block. Experimental results achieved a 14.59%, on average, time-saving, and a 0.69% and a 0.19 dB loss for bit-rate and PSNR, respectively.

Complexity reduction algorithm for prediction unit decision process in high efficiency video coding

To provide very high quality and/or high resolution video content under limited bandwidth conditions for transmission or storage, the high efficiency video coding (HEVC) has been recently finalised by the joint collaborative team on video coding. In this study, the authors propose a fast prediction unit (PU) decision method to reduce the computational complexity of HEVC encoder. They use an early PU decision in each coding unit-level based on spatio-temporal analyses and depth correlations. They also consider a classification of motion activity. Experimental results show that the encoding complexity can be reduced by up to 38% on average in the random access main profile configuration with only a small bit-rate increment and a peak signal to noise ratio (PSNR) decrement, compared to high efficiency video coding test model (HM) 7.0 reference software.

Fast Coding Algorithm for High Efficient Video Coding (HEVC)

The JCT-VC is developing the next-generation video coding standard which is called a high efficiency video coding (HEVC). In the HEVC, there are three unit in block structure: coding unit (CU), prediction unit (PU), and transform unit (TU). The CU is the basic unit of region splitting like macroblock. The CU concept perform recursive splitting into four blocks with equal size, starting from the treeblock. We use mode information of the current CU to avoid unnecessary CU splitting process. To reduce more computational complexity, we propose a depth range selection mechanism (DRSM) by selecting adaptive depth range. The depth range selection mechanism provides an effective splitting by performing just CUs in want of process. The experimental results show that the proposed algorithm can achieve about 48 % of reduction in encoding time for RandomAccess HE compared to the HEVC test model (HM) 6.0 encoder with BD-bitrate loss of 1.2 %.

Fast mode decision scheme using sum of the absolute difference-based Bayesian model for the H.264/AVC video standard

H.264/AVC is the most widely used recent video coding standard. It provides a high encoding efficiency but it also has a high computational complexity. The block mode decision for motion estimation is the most time-consuming procedure. A complexity reduction method for the block mode decision procedure is proposed. To reduce the complexity, all block modes are divided into several candidate block mode groups. The sum of the absolute difference (SAD) value, including the motion cost of each mode, is used as a classification feature to divide the block modes into several groups. A refinement method using a Bayesian model based on the average SAD value is also proposed. For B-slices, a differential block mode allocation method is suggested. A different number of candidate modes are allocated for lists (list 0, list 1) based on the SAD value of each list after 16 × 16 block motion estimation. The proposed method achieves an average time-saving for the total encoding time of 65% for IPPP and 66.01% for the hierarchical-B structure.

Fast video encoding algorithm for the Internet of Things environment based on high efficiency video coding

Video data for the Internet traffic is increasing, and video data transmission is important for consideration of real-time process in the Internet of Things (IoT). Thus, in the IoT environment, video applications will be valuable approach in networks of smart sensor devices. High Efficiency Video Coding (HEVC) has been developed by the Joint Collaborative Team on Video Coding (JCT-VC) as a new generation video coding standard. Recently, HEVC includes range extensions (RExt), scalable coding extensions, and multiview extensions. HEVC RExt provides high resolution video with a high bit-depth and an abundance of color formats. In this paper, a fast intraprediction unit decision method is proposed to reduce the computational complexity of the HEVC RExt encoder. To design intramode decision algorithm, Local Binary Pattern (LBP) of the current prediction unit is used as texture feature. Experimental results show that the encoding complexity can be reduced by up to 12.35% on average in the AI-Main profile configuration with only a small bit-rate increment and a PSNR decrement, compared with HEVC test model (HM) 12.0-RExt4.0 reference software.