Fast Mode Decision Algorithms for High Efficiency Video Coding (HEVC) and Image Matting
Author : Yongfang Shi
Publisher :
Page : 65 pages
File Size : 16,75 MB
Release : 2013
Category : Digital video
ISBN :
High Efficiency Video Coding (HEVC)
Author : Vivienne Sze
Publisher : Springer
Page : 384 pages
File Size : 25,32 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.
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 : 43,11 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.
High Efficiency Video Coding and Other Emerging Standards
Author : K.R. Rao
Publisher : River Publishers
Page : 320 pages
File Size : 12,61 MB
Release : 2017-07-21
Category : Computers
ISBN : 8793609035
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.
Fast Intra/ Inter Mode Decision Algorithms for High Efficiency Video Coding (HEVC)
Author : Junaid Tariq
Publisher :
Page : 151 pages
File Size : 14,56 MB
Release : 2016
Category : Digital video
ISBN :
Book Description
Complexity-Aware High Efficiency Video Coding
Author : Guilherme Corrêa
Publisher : Springer
Page : 246 pages
File Size : 13,53 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.
Fast Intra-frame Coding Algorithm for HEVC Based on TCM and Machine Learning
Author : Yi Shan
Publisher :
Page : 69 pages
File Size : 39,13 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.
Versatile Video Coding: Latest Advances in Video Coding Standards
Author : Ochoa Dominguez, Humberto
Publisher : River Publishers
Page : 460 pages
File Size : 13,76 MB
Release : 2019-03-08
Category : Technology & Engineering
ISBN : 8770220476
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
Multilayers Fast Mode Decision Algorithm for Scalable Video Coding
Author : Haris Al Qodri Maarif
Publisher : LAP Lambert Academic Publishing
Page : 120 pages
File Size : 25,39 MB
Release : 2011-08
Category :
ISBN : 9783845470184
Book Description
Scalable Video Coding (SVC) is the extension of H.264/AVC. It has higher coding complexity and encoding time in SVC encoder. SVC is gaining great interest because of its ability and scalability to adapt in various network conditions. SVC allows partial transmission and decoding of a bitstream. This research deals with the fast mode decision algorithm for decreasing encoding time or fastening the mode decision process of the SVC encoder. Moreover, the performance of SVC over IEEE 802.11g wireless LAN has been evaluated using Scalable Video Evaluation Framework (SVEF). The fast mode decision scheme has been implemented and successfully decreased encoding time with negligible loss of the quality and bitrate requirements. The streaming simulation has also been performed using the SVEF simulator. The simulation result shows the proposed fast mode decision algorithm provides time saving up to 45% while maintaining video quality with negligible PSNR loss.
Efficient Predictive Algorithms for Image Compression
Author : Luís Filipe Rosário Lucas
Publisher : Springer
Page : 180 pages
File Size : 31,50 MB
Release : 2017-02-09
Category : Technology & Engineering
ISBN : 3319511807
Book Description
This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is investigated for compression of Light Field images based on the HEVC technology. A new linear prediction method using sparse constraints is also described, enabling improved coding performance of the HEVC standard, particularly for images with complex textures based on repeated structures. Finally, the authors present a new, generalized intra-prediction framework for the HEVC standard, which unifies the directional prediction methods used in the current video compression standards, with linear prediction methods using sparse constraints. Experimental results for the compression of natural images are provided, demonstrating the advantage of the unified prediction framework over the traditional directional prediction modes used in HEVC standard.
