A novel motion classification based intermode selection strategy for HEVC performance improvement

High Efficiency Video Coding (HEVC) standard adopts several new approaches to achieve higher coding efficiency (approximately 50% bit-rate reduction) compared to its predecessor H.264/AVC with same perceptual image quality. Huge computational time has also increased due to the algorithmic complexity of HEVC compared to H.264/AVC. However, it is really a demanding task to reduce the encoding time while preserving the similar quality of the video sequences. In this paper, we propose a novel efficient intermode selection technique and incorporate into HEVC framework to predict motion estimation and motion compensation modes between current and reference blocks and perform faster inter mode selection based on three dissimilar motion types in divergent video sequences. Instead of exploring and traversing all the modes exhaustively, we merely select a subset of candidate modes and the final mode from the selected subset is determined based on their lowest Lagrangian cost function. The experimental results reveal that average encoding time can be downscaled by 40% with similar rate-distortion performance compared to the exhaustive mode selection strategy in HEVC

Efficient HEVC scheme using motion type categorization

High Efficiency Video Coding (HEVC) standard introduces a number of innovative tools which can reduce approximately 50% bit-rate compared to its predecessor H.264/AVC at the same perceptual video quality whereas the computational time has increased multiple times. To reduce the encoding time while preserving the expected video quality has become a real challenge today for video transmission and streaming especially using low-powered devices. Motion estimation (ME) and motion compensation (MC) using variable-size blocks (i.e., intermodes) require 60-80% of total computational time. In this paper we propose a new efficient intermode selection technique based on phase correlation and incorporate into HEVC framework to predict ME and MC modes and perform faster intermode selection based on three dissimilar motion types in different videos. Instead of exploring all the modes exhaustively we select a subset of modes using motion type and the final mode is selected based on the Lagrangian cost function. The experimental results show that compared to HEVC the average computational time can be downscaled by 34% while providing the similar rate-distortion (RD) performance

Fast coding strategy for HEVC by motion features and saliency applied on difference between successive image blocks

Introducing a number of innovative and powerful coding tools, the High Efficiency Video Coding (HEVC) standard promises double compression efficiency, compared to its predecessor H.264, with similar perceptual quality. The increased computational time complexity is an important issue for the video coding research community as well. An attempt to reduce this complexity of HEVC is adopted in this paper, by efficient selection of appropriate block-partitioning modes based on motion features and the saliency applied to the difference between successive image blocks. As this difference gives us the explicit visible motion and salient information, we develop a cost function by combining the motion features and image difference salient feature. The combined features are then converted into area of interest (AOI) based binary pattern for the current block. This pattern is then compared with a previously defined codebook of binary pattern templates for a subset of mode selection. Motion estimation (ME) and motion compensation (MC) are performed only on the selected subset of modes, without exhaustive exploration of all modes available in HEVC. The experimental results reveal a reduction of 42% encoding time complexity of HEVC encoder with similar subjective and objective image quality

Fast mode decision in the HEVC Video coding standard by exploiting region with dominated motion and saliency features

The emerging High Efficiency Video Coding (HEVC) standard introduces a number of innovative and powerful coding tools to acquire better compression efficiency compared to its predecessor H.264. The encoding time complexities have also increased multiple times that is not suitable for realtime video coding applications. To address this limitation, this paper employs a novel coding strategy to reduce the time complexity in HEVC encoder by efficient selection of appropriate block-partitioning modes based on human visual features (HVF). The HVF in the proposed technique comprise with human visual attention modelling-based saliency feature and phase correlation-based motion features. The features are innovatively combined through a fusion process by developing a content-based adaptive weighted cost function to determine the region with dominated motion/saliency (RDMS)- based binary pattern for the current block. The generated binary pattern is then compared with a codebook of predefined binary pattern templates aligned to the HEVC recommended block-paritioning to estimate a subset of inter-prediction modes. Without exhaustive exploration of all modes available in the HEVC standard, only the selected subset of modes are motion estimated and motion compensated for a particular coding unit. The experimental evaluation reveals that the proposed technique notably down-scales the average computational time of the latest HEVC reference encoder by 34% while providing similar rate-distortion (RD) performance for a wide range of video sequences

Efficient video coding using visual sensitive information for HEVC coding standard

The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos

Alogorithms for fast implementation of high efficiency video coding

Recently, there is higher demand for video content in multimedia communication, which leads to increased requirements for storage and bandwidth posed to internet service providers. Due to this, it became necessary for the telecommunication standardization sector of the International Telecommunication Union (ITU-T) to launch a new video compression standard that would address the twin challenges of lowering both digital file sizes in storage media and transmission bandwidths in networks. The High Efficiency Video Compression (HEVC) also known as H.265 standard was launched in November 2013 to address these challenges. This new standard was able to cut down, by 50%, on existing media file sizes and bandwidths but its computational complexity leads to about 400% delay in HEVC video encoding. This study proposes a solution to the above problem based on three key areas of the HEVC. Firstly, two fast motion estimation algorithms are proposed based on triangle and pentagon structures to implement motion estimation and compensation in a shorter time. Secondly, an enhanced and optimized inter-prediction mode selection is proposed. Thirdly, an enhanced intra-prediction mode scheme with reduced latency is suggested. Based on the test model of the HEVC reference software, each individual algorithm manages to reduce the encoding time across all video classes by an average of 20-30%, with a best reduction of 70%, at a negligible loss in coding efficiency and video quality degradation. In practice, these algorithms would be able to enhance the performance of the HEVC compression standard, and enable higher resolution and higher frame rate video encoding as compared to the stateof- the-art technique

Efficient compression of synthetic video

Streaming of on-line gaming video is a challenging problem because of the enormous amounts of video data that need to be sent during game playing, especially within the limitations of uplink capabilities. The encoding complexity is also a challenge because of the time delay while on-line gamers are communicating. The main goal of this research study is to propose an enhanced on-line game video streaming system. First, the most common video coding techniques have been evaluated. The evaluation study considers objective and subjective metrics. Three widespread video coding techniques are selected and evaluated in the study; H.264, MPEG-4 Visual and VP- 8. Diverse types of video sequences were used with different frame rates and resolutions. The effects of changing frame rate and resolution on compression efficiency and viewers‟ satisfaction are also presented. Results showed that the compression process and perceptual satisfaction are severely affected by the nature of the compressed sequence. As a result, H.264 showed higher compression efficiency for synthetic sequences and outperformed other codecs in the subjective evaluation tests. Second, a fast inter prediction technique to speed up the encoding process of H.264 has been devised. The on-line game streaming service is a real time application, thus, compression complexity significantly affects the whole process of on-line streaming. H.264 has been recommended for synthetic video coding by our results gained in codecs comparative studies. However, it still suffers from high encoding complexity; thus a low complexity coding algorithm is presented as fast inter coding model with reference management technique. The proposed algorithm was compared to a state of the art method, the results showing better achievement in time and bit rate reduction with negligible loss of fidelity. Third, recommendations on tradeoff between frame rates and resolution within given uplink capabilities are provided for H.264 video coding. The recommended tradeoffs are offered as a result of extensive experiments using Double Stimulus Impairment Scale (DSIS) subjective evaluation metric. Experiments showed that viewers‟ satisfaction is profoundly affected by varying frame rates and resolutions. In addition, increasing frame rate or frame resolution does not always guarantee improved increments of perceptual quality. As a result, tradeoffs are recommended to compromise between frame rate and resolution within a given bit rate to guarantee the highest user satisfaction. For system completeness and to facilitate the implementation of the proposed techniques, an efficient game video streaming management system is proposed. Compared to existing on-line live video service systems for games, the proposed system provides improved coding efficiency, complexity reduction and better user satisfaction

Fast Intermode Selection for HEVC Video Coding Using Phase Correlation

The recent High Efficiency Video Coding (HEVC) Standard demonstrates higher rate-distortion (RD) performance compared to its predecessor H.264/AVC using different new tools especially larger and asymmetric inter-mode variable size motion estimation and compensation. This requires more than 4 times computational time compared to H.264/AVC. As a result it has always been a big concern for the researchers to reduce the amount of time while maintaining the standard quality of the video. The reduction of computational time by smart selection of the appropriate modes in HEVC is our motivation. To accomplish this task in this paper, we use phase correlation to approximate the motion information between current and reference blocks by comparing with a number of different binary pattern templates and then select a subset of motion estimation modes without exhaustively exploring all possible modes. The experimental results exhibit that the proposed HEVC-PC (HEVC with Phase Correlation) scheme outperforms the standard HEVC scheme in terms of computational time while preserving-the same quality of the video sequences. More specifically, around 40% encoding time is reduced compared to the exhaustive mode selection in HEVC