Mode decision for the H.264/AVC video coding standard

H.264/AVC video coding standard gives us a very promising future for the field of video broadcasting and communication because of its high coding efficiency compared with other older video coding standards. However, high coding efficiency also carries high computational complexity. Fast motion estimation and fast mode decision are two very useful techniques which can significantly reduce computational complexity. This thesis focuses on the field of fast mode decision. The goal of this thesis is that for very similar RD performance compared with H.264/AVC video coding standard, we aim to find new fast mode decision techniques which can afford significant time savings. [Continues.

An efficient fast mode decision algorithm for H.264/AVC intra/inter predictions

H.264/AVC is the newest video coding standard, which outperforms the former standards in video coding efficiency in terms of improved video quality and decreased bitrate. Variable block size based mode decision (MD) with rate distortion optimization (RDO) is one of the most impressive new techniques employed in H.264/AVC. However, the improvement on performance is achieved at the expense of significantly increased computational complexity, which is a key challenge for real-time applications. An efficient fast mode decision algorithm is then proposed in this paper. By exploiting the correlation between macroblocks and the statistical characteristics of sub-macroblock in MD, the video encoding time can be reduced 52.19% on average. Furthermore, the motion speed based adjustment scheme was introduced to minimize the degradation of performanc

Multilayers Fast Mode Decision Algorithms for Scalable Video Coding

Abstract: Scalable video coding (SVC) is the extension of H.264/AVC standard. The features in SVC are also developed from the H.264/AVC standard, so that SVC has more features compared to H.264/AVC standard. This provides higher coding complexity in SVC encoder which causes higher encoding time for SVC. 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 multilayers fast mode decision algorithm for decreasing encoding time or fastening the mode decision process of the SVC encoder. The proposed fast mode decision scheme has been implemented and is successfully decrease encoding time with negligible loss of quality and bitrate requirement. The simulation result shows the proposed fast mode decision algorithm provides time saving up to 45 % while maintaining video quality with negligible PSNR loss

Fast intra mode decision algorithm for H.263 to H.264/AVC transcoding

2007-2008 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Very low complexity mpeg-2 to h.264 transcoding using machine learning

ABSTRACT This paper presents a novel macroblock mode decision algorithm for inter-frame prediction based on machine learning techniques to be used as part of a very low complexity MPEG-2 to H.264 video transcoder. Since coding mode decisions take up the most resources in video transcoding, a fast macro block (MB) mode estimation would lead to reduced complexity. The proposed approach is based on the hypothesis that MB coding mode decisions in H.264 video have a correlation with the distribution of the motion compensated residual in MPEG-2 video. We use machine learning tools to exploit the correlation and derive decision trees to classify the incoming MPEG-2 MBs into one of the 11 coding modes in H.264. The proposed approach reduces the H.264 MB mode computation process into a decision tree lookup with very low complexity. The proposed transcoder is compared with a reference transcoder comprised of a MPEG-2 decoder and an H.264 encoder. Our results show that the proposed transcoder reduces the H.264 encoding time by over 95% with negligible loss in quality and bitrate

Fast Mode Decision on H.264/AVC Baseline Profile for real-time performance

In this paper a new fast mode decision (FMD) algorithm is proposed for the recent H.264/AVC video coding standard, aiming to reduce its computational load without loosing coding efficiency. This algorithm identifies redundancy and selects the minimum sub-set of modes for each macroblock (MB) required to provide high rate-distortion (RD) efficiency. It is based on a fast analysis of the histogram of the difference image between frames which classifies the areas of each frame as active or non-active by means of an adaptive thresholding technique. More coding effort is devoted to active areas with the selection of a large sub-set of Modes, as these areas are expected to be the most relevant in terms of RD cost. Results show reduction values around 35–65% of motion estimation (ME) time, preserving the RD cost for the Baseline Profile, by using P-Slices and without needing B-Slices. Moreover, the strategy works as an intelligent tool for real-time applications with constrained number of operations per frame: it wisely uses the given operational resources distributing them among those MBs that need it

A New Fast Motion Estimation and Mode Decision algorithm for H.264 Depth Maps encoding in Free Viewpoint TV

In this paper, we consider a scenario where 3D scenes are modeled through a View+Depth representation. This representation is to be used at the rendering side to generate synthetic views for free viewpoint video. The encoding of both type of data (view and depth) is carried out using two H.264/AVC encoders. In this scenario we address the reduction of the encoding complexity of depth data. Firstly, an analysis of the Mode Decision and Motion Estimation processes has been conducted for both view and depth sequences, in order to capture the correlation between them. Taking advantage of this correlation, we propose a fast mode decision and motion estimation algorithm for the depth encoding. Results show that the proposed algorithm reduces the computational burden with a negligible loss in terms of quality of the rendered synthetic views. Quality measurements have been conducted using the Video Quality Metric

Fast Mode Decision Algorithms for Adaptive GOP Structure in the Scalable Extension of H.264/AVC

[[abstract]]We propose a fast mode decision algorithm to reduce the computational complexity of adaptive GOP structure (AGS) in the scalable extension of H.264/AVC. AGS can improve the coding efficiency of the scalable extension of H.264. It, however, needs to perform motion-compensated temporal filtering (MCTF) of all possible GOP sizes, leading to much higher computation than the fixed GOP structure. In our proposed algorithm, after performing the MCTF with the maximum GOP size, we utilize two features to decide whether to perform the remaining MCTFs of sub-GOPs and mode selection. Experimental results show that the proposed algorithm can significantly reduce unnecessary MCTF computation for AGS, while maintaining good coding efficiency.[[fileno]]2030144030011[[department]]電機工程學

Multilayers fast mode decision algorithm for scalable video coding: design, implementation, and streaming evaluation on IEEE 802.11g wireless LAN

Nowadays the advancement of technologies has reached the massive growth and commercial success in multimedia and mobile communication. The advancement and development in video coding technology, together with the increase of storage capacity network infrastructures and computing power are enabling an increasing number of video applications. Scalable video coding (SVC) is the extension of H.264/AVC standard. The features in SVC are also developed from the H.264/AVC standard, so that SVC has more features compared to H.264/AVC standard. This provides higher coding complexity in SVC encoder which causes higher encoding time for SVC. 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 fast mode decision algorithm for decreasing encoding time or fastening the mode decision process of the SVC encoder. Moreover, the performance of SVC over wireless network will be evaluated. The simulation tools can be of great help for a better understanding of the streaming analysis over the network. Hence, this research utilizes Scalable Video Evaluation Framework (SVEF). The fast mode decision scheme has been implemented and successfully decreased encoding time with negligible loss of quality and bitrate requirement. 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. For the streaming video, the received packets on the receiver can be reconstructed on maintained video quality with also negligible PSNR loss