Fast Intra/ Inter Mode Decision Algorithms for High Efficiency Video Coding (HEVC)
Author : Junaid Tariq
Publisher :
Page : 151 pages
File Size : 39,5 MB
Release : 2016
Category : Digital video
ISBN :
High Efficiency Video Coding (HEVC)
Author : Vivienne Sze
Publisher : Springer
Page : 384 pages
File Size : 18,89 MB
Release : 2014-08-23
Category : Technology & Engineering
ISBN : 3319068954
Book Description
This book provides developers, engineers, researchers and students with detailed knowledge about the High Efficiency Video Coding (HEVC) standard. HEVC is the successor to the widely successful H.264/AVC video compression standard, and it provides around twice as much compression as H.264/AVC for the same level of quality. The applications for HEVC will not only cover the space of the well-known current uses and capabilities of digital video – they will also include the deployment of new services and the delivery of enhanced video quality, such as ultra-high-definition television (UHDTV) and video with higher dynamic range, wider range of representable color, and greater representation precision than what is typically found today. HEVC is the next major generation of video coding design – a flexible, reliable and robust solution that will support the next decade of video applications and ease the burden of video on world-wide network traffic. This book provides a detailed explanation of the various parts of the standard, insight into how it was developed, and in-depth discussion of algorithms and architectures for its implementation.
Fast Intra-frame Coding Algorithm for HEVC Based on TCM and Machine Learning
Author : Yi Shan
Publisher :
Page : 69 pages
File Size : 13,32 MB
Release : 2016
Category : Digital video
ISBN :
Book Description
High Efficiency Video Coding (HEVC) is the latest video coding standard. Compared with the previous standard H.264/AVC, it can reduce the bit-rate by around 50% while maintaining the same perceptual quality. This performance gain on compression is achieved mainly by supporting larger Coding Unit (CU) size and more prediction modes. However, since the encoder needs to traverse all possible choices to mine out the best way of encoding data, this large flexibility on block size and prediction modes has caused a tremendous increase in encoding time. In HEVC, intra-frame coding is an important basis, and it is widely used in all configurations. Therefore, fast algorithms are always required to alleviate the computational complexity of HEVC intra-frame coding. In this thesis, a fast intra-frame coding algorithm based on machine learning is proposed to predict CU decisions. Hence the computational complexity can be significantly reduced with negligible loss in the coding efficiency. Machine learning models like Bayes decision, Support Vector Machine (SVM) are used as decision makers while the Laplacian Transparent Composite Model (LPTCM) is selected as a feature extraction tool. In the main version of the proposed algorithm, a set of features named with Summation of Binarized Outlier Coefficients (SBOC) is extracted to train SVM models. An online training structure and a performance control method are introduced to enhance the robustness of decision makers. When applied on All Intra Main (AIM) full test and compared with HM 16.3, the main version of the proposed algorithm can achieve, on average, 48% time reduction with 0.78% BD-rate increase. Through adjusting parameter settings, the algorithm can change the trade-off between encoding time and coding efficiency, which can generate a performance curve to meet different requirements. By testing different methods on the same machine, the performance of proposed method has outperformed all CU decision based HEVC fast intra-frame algorithms in the benchmarks.
Fast Mode Decision Algorithms for High Efficiency Video Coding (HEVC) and Image Matting
Author : Yongfang Shi
Publisher :
Page : 65 pages
File Size : 42,31 MB
Release : 2013
Category : Digital video
ISBN :
Book Description
Complexity-Aware High Efficiency Video Coding
Author : Guilherme Corrêa
Publisher : Springer
Page : 246 pages
File Size : 15,72 MB
Release : 2015-12-29
Category : Technology & Engineering
ISBN : 3319257781
Book Description
This book discusses computational complexity of High Efficiency Video Coding (HEVC) encoders with coverage extending from the analysis of HEVC compression efficiency and computational complexity to the reduction and scaling of its encoding complexity. After an introduction to the topic and a review of the state-of-the-art research in the field, the authors provide a detailed analysis of the HEVC encoding tools compression efficiency and computational complexity. Readers will benefit from a set of algorithms for scaling the computational complexity of HEVC encoders, all of which take advantage from the flexibility of the frame partitioning structures allowed by the standard. The authors also provide a set of early termination methods based on data mining and machine learning techniques, which are able to reduce the computational complexity required to find the best frame partitioning structures. The applicability of the proposed methods is finally exemplified with an encoding time control system that employs the best complexity reduction and scaling methods presented throughout the book. The methods presented in this book are especially useful in power-constrained, portable multimedia devices to reduce energy consumption and to extend battery life. They can also be applied to portable and non-portable multimedia devices operating in real time with limited computational resources.
High Efficiency Video Coding and Other Emerging Standards
Author : K.R. Rao
Publisher : CRC Press
Page : 319 pages
File Size : 36,9 MB
Release : 2022-09-01
Category : Technology & Engineering
ISBN : 1000794636
Book Description
High Efficiency Video Coding and Other Emerging Standards provides an overview of high efficiency video coding (HEVC) and all its extensions and profiles. There are nearly 300 projects and problems included, and about 400 references related to HEVC alone. Next generation video coding (NGVC) beyond HEVC is also described. Other video coding standards such as AVS2, DAALA, THOR, VP9 (Google), DIRAC, VC1, and AV1 are addressed, and image coding standards such as JPEG, JPEG-LS, JPEG2000, JPEG XR, JPEG XS, JPEG XT and JPEG-Pleno are also listed.Understanding of these standards and their implementation is facilitated by overview papers, standards documents, reference software, software manuals, test sequences, source codes, tutorials, keynote speakers, panel discussions, reflector and ftp/web sites – all in the public domain. Access to these categories is also provided.
Deep Learning Based Fast Mode Decision in HEVC Intra Prediction Using Region Wise Feature Classification
Author : Shiba Prasad Kuanar
Publisher :
Page : 53 pages
File Size : 44,19 MB
Release : 2019
Category : Artificial intelligence
ISBN :
Book Description
The High Efficiency Video Coding (HEVC) standard has achieved best coding efficiency as compared to previous H.264/AVC standard. But the computational time of HEVC encoder has increased mainly because of the hierarchical quad-tree based structure, recursive search for finding the best coding units, and the exhaustive prediction search up-to 35 modes. These advances improve the coding efficiency, but result into a very high computational complexity. Furthermore selecting the optimal modes among all prediction modes are necessary for the subsequent rate distortion optimization process. Therefore we propose a convolutional neural network (CNN) based algorithm which learns the region wise image features and performs a classification job. These classification results are later used in the encoder downstream systems for finding the optimal coding units in each of the tree blocks, and subsequently reduce the number of prediction modes. For our model training, we gathered a new dataset which includes diverse images for the better generalization of our results. The experimental results show that our proposed learning based algorithm reduces the encoder time up to 66.15 % with a minimal Bjontegaard Delta Bit Rate (BD-BR) loss of 1.34 %over the state-of-the-art machine learning approaches. Furthermore our method also reduces the mode selection by 45.91 % with respect to the HEVC baseline.
Reducing the Compexity of Inter-prediction Mode Decision for High Effeciency Video Codec
Author : Kushal Shah
Publisher :
Page : 77 pages
File Size : 39,29 MB
Release : 2014
Category :
ISBN :
Book Description
The High Efficiency Video Coding (HEVC) standard is the latest joint video project of the International Telecommunication Unit (ITU-T) Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) standardization organizations, working together in a partnership known as the Joint Collaborative Team on Video Coding (JCT-VC). While the HEVC is based on the same architecture of the widely used H.264/AVC (Advance Video Coding) standard [8], it includes many new coding tools, and almost all the encoder blocks are optimized with respect to their counterparts in the H.264/AVC standard. This allows the new standard to achieve up to 50% bitrate reduction compared to its predecessor with the same visual quality at the cost of increased complexity [1]. Like H.264/AVC, mode decisions with Motion Estimation (ME) remain among the most time-consuming computations in HEVC. In an inter-prediction mode decision, a fullsearch algorithm searches for every possible block size and refines the results from integer-pel to quarter-pel resolution. Thus, a full-search algorithm guarantees the highest level of compression performance. However, the considerable computational complexity for a mode decision decreases the encoding speed. In this thesis a fast adaptive termination [20] algorithm is proposed that terminates early the mode decision in inter-prediction for HEVC. Based on Rate Distortion (RD) cost, all the inter prediction modes are classified as skip or non-skip modes, and to select the best mode minimum RD cost of these two modes are predicted. For skip mode, the mode decision is predicted in early stage while in non-skip mode different stages are proposed to speed-up the mode decision. Experimental results based on several video test sequences suggest a decrease of about 25%-40% in encoding time is achieved with implementation of the Fast Adaptive Termination algorithm for interprediction mode decision with negligible degradation in peak signal to noise ratio (PSNR). Metrics such as BD-bitrate (Bjøntegaard Delta bitrate), BD-PSNR (Bjøntegaard Delta Peak Signal to Noise Ratio), SSIM (Structural Similarity) and computational complexity are also used.
Fast Intra Mode Decision in High Efficiency Video Coding
Author : Harshdeep Brahmasury Jain
Publisher :
Page : 66 pages
File Size : 10,30 MB
Release : 2014
Category :
ISBN :
Book Description
In this thesis a CU early termination algorithm with a fast intra prediction algorithm is proposed that terminates complete full search prediction for the CU and replaced by CU early termination algorithm which determines the complexity of the CU block then on sent decision is made to further split or non-split the CU. This is followed by a PU mode decision to find the optimal modes prediction mode from 35 prediction modes. This includes a two-step process: firstly calculating the Sum of Absolute Differences (SAD) of all the modes by down sampling method and secondly applying a three step search algorithm to remove unnecessary modes. This is followed by early RDOQ (Rate Distortion Optimization Quantization) termination algorithm to further reduce the encoding time. Experimental results based on several video test sequences suggest a decrease of about 35%-48% in encoding time is achieved with implementation of the proposed CU early termination algorithm and fast intra mode decision algorithm for intra predication mode decision with negligible degradation in peak signal to noise ratio (PSNR). Metrics such as BD-bitrate (Bjøntegaard Delta bitrate), BD-PSNR (Bjøntegaard Delta Peak Signal to Noise Ratio) and RD curve (Rate Distortion) are also used.
Versatile Video Coding
Author : Humberto Ochoa Dominguez
Publisher : CRC Press
Page : 458 pages
File Size : 48,54 MB
Release : 2022-09-01
Category : Technology & Engineering
ISBN : 1000795055
Book Description
Video is the main driver of bandwidth use, accounting for over 80 per cent of consumer Internet traffic. Video compression is a critical component of many of the available multimedia applications, it is necessary for storage or transmission of digital video over today's band-limited networks. The majority of this video is coded using international standards developed in collaboration with ITU-T Study Group and MPEG. The MPEG family of video coding standards begun on the early 1990s with MPEG-1, developed for video and audio storage on CD-ROMs, with support for progressive video. MPEG-2 was standardized in 1995 for applications of video on DVD, standard and high definition television, with support for interlaced and progressive video. MPEG-4 part 2, also known as MPEG-2 video, was standardized in 1999 for applications of low- bit rate multimedia on mobile platforms and the Internet, with the support of object-based or content based coding by modeling the scene as background and foreground. Since MPEG-1, the main video coding standards were based on the so-called macroblocks. However, research groups continued the work beyond the traditional video coding architectures and found that macroblocks could limit the performance of the compression when using high-resolution video. Therefore, in 2013 the high efficiency video coding (HEVC) also known and H.265, was released, with a structure similar to H.264/AVC but using coding units with more flexible partitions than the traditional macroblocks. HEVC has greater flexibility in prediction modes and transform block sizes, also it has a more sophisticated interpolation and de blocking filters. In 2006 the VC-1 was released. VC-1 is a video codec implemented by Microsoft and the Microsoft Windows Media Video (VMW) 9 and standardized by the Society of Motion Picture and Television Engineers (SMPTE). In 2017 the Joint Video Experts Team (JVET) released a call for proposals for a new video coding standard initially called Beyond the HEVC, Future Video Coding (FVC) or known as Versatile Video Coding (VVC). VVC is being built on top of HEVC for application on Standard Dynamic Range (SDR), High Dynamic Range (HDR) and 360° Video. The VVC is planned to be finalized by 2020. This book presents the new VVC, and updates on the HEVC. The book discusses the advances in lossless coding and covers the topic of screen content coding. Technical topics discussed include: Beyond the High Efficiency Video CodingHigh Efficiency Video Coding encoderScreen contentLossless and visually lossless coding algorithmsFast coding algorithmsVisual quality assessmentOther screen content coding algorithmsOverview of JPEG Series
