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The latest international video coding standard, H.266/Versatile Video Coding (VVC), supports high-definition videos, with resolutions from 4 K to 8 K or even larger. It offers a higher compression ratio than its predecessor, H.265/High Efficiency Video Coding (HEVC). In addition to the quadtree partition structure of H.265/HEVC, the nested multi-type tree (MTT) structure of H.266/VVC provides more diverse splits through binary and ternary trees. It also includes many new coding tools, which tremendously increases the encoding complexity. This paper proposes a fast intra coding algorithm for H.266/VVC based on visual perception analysis. The algorithm applies the factor of average background luminance for just-noticeable-distortion to identify the visually distinguishable (VD) pixels within a coding unit (CU). We propose calculating the variances of the numbers of VD pixels in various MTT splits of a CU. Intra sub-partitions and matrix weighted intra prediction are turned off conditionally based on the variance of the four variances for MTT splits and a thresholding criterion. The fast horizontal/vertical splitting decisions for binary and ternary trees are proposed by utilizing random forest classifiers of machine learning techniques, which use the information of VD pixels and the quantization parameter. Experimental results show that the proposed algorithm achieves around 47.26% encoding time reduction with a Bjøntegaard Delta Bitrate (BDBR) of 1.535% on average under the All Intra configuration. Overall, this algorithm can significantly speed up H.266/VVC intra coding and outperform previous studies. [ABSTRACT FROM AUTHOR]

This paper designs a novel method to reduce the coding complexity of 3D‐HEVC encoder by utilizing the properties of human visual perception. Two vision‐oriented edge detections are proposed: for colour texture detection, the authors adopt the Just‐Noticeable Distortion (JND); for depth map, the authors combine the Sample Adaptive Offset (SAO) and the Just Noticeable Depth Difference (JNDD) model. The authors also analyse the properties of colour texture and depth map to classify the coding tree unit (CTU) into various kinds of types, including complex‐edge CTU, moderate‐edge CTU and homogeneous CTU. Besides, fast mode decisions and early termination criteria are performed individually on each type of CTUs according to their characteristics. Especially for those CTUs with more edge information, the proposed projection‐based fast mode decision and residual‐based early termination preserve important colour texture while speeding up the coding at the same time. The proposed vision‐oriented algorithm reduces 31.981% of the overall average coding time with only 1.580% BD‐Bitrate increase. Experimental results show that the proposed algorithm can provide considerable time‐saving while still maintain the video quality, which outperforms the previous researches. [ABSTRACT FROM AUTHOR]

The 3D extension of High Efficiency Video Coding (3D-HEVC) is the latest international 3D video coding standard, which enhances the compression efficiency of 3D videos with multi-view plus depth (MVD) format. However, it is at the cost of increasing coding complexity. Therefore, this paper proposes a fast inter-prediction algorithm based on depth segmentation for the depth coding of 3D-HEVC to reduce the coding complexity of the depth map. We aim to reduce the coding time by efficiently utilizing the properties of the depth map. First, the proposed algorithm divides a depth map into background, middle ground and foreground, based on automatic thresholding technique. Then, we adjust the search range according to the classification of the coding tree unit (CTU). In addition, an early termination decision by utilizing the correlation of spatial, temporal, and inter-view neighboring CTUs and a fast prediction unit mode decision are also proposed to reduce coding time. The experimental results show that the proposed algorithm can reduce the depth coding time and still maintain good video quality. [ABSTRACT FROM AUTHOR]

The latest video coding standard, high efficiency video coding (HEVC), aims to achieve better coding efficiency than the H.264/AVC standard. To improve the coding performance of HEVC, tools and structures are included that also increase the computational complexity of encoding, especially for the mode decisions in the coding unit (CU), which is a structural element in the HEVC. For each CU size, the HEVC encoder performs mode decision and motion estimation using all prediction unit (PU) types and incurs massive computational burdens. In this paper, we investigate the depth correlation between the current and the collocated CU to avoid irrelevant CU procedure and truncate some PU predictions as a result. We also investigate the relationship of the rate-distortion (RD) costs after the Merge/SKIP prediction. By analyzing different CU sizes and quantization parameters, we build a mathematical model to represent the relationship for the RD costs after the Merge/SKIP prediction with an adaptive termination of the CU procedure. In addition, the relationship of the RD costs after the Merge/SKIP prediction and 2N \boldsymbol \times 2\textN mode is also explored. Search range reduction is used to further speed up our algorithm. Experimental results show that our algorithm can reduce the coding time by up to 80%, and provide average coding time savings of 46%, 45%, and 52%, for low delay B, low delay P, and random access configurations, respectively. Moreover, the proposed algorithm is able to maintain coding performance similar to HM 11.0. The proposed scheme outperforms previous work in terms of both the coding speed and the RD performance. [ABSTRACT FROM PUBLISHER]

In this paper, a whole frame loss error concealment algorithm for three-dimensional video coding is proposed. The main concept of the proposed algorithm is to extrapolate the motion vectors for concealing a current error block by jointly considering the available motion vector and the depth information. In addition, the depth information is adopted to help the derivation of reference pixels for concealing errors in the case that suitable motion vectors cannot be obtained by the motion vector extrapolation process alone. Simulation results demonstrate that our proposed algorithm can achieve up to 0.52 dB PSNR, as well as subjective quality improvement, compared to previous work. [ABSTRACT FROM PUBLISHER]

ABSTRACT This article proposed an accurate disparity vector prediction (DVP) algorithm for multi-view video coding. Differing from traditional DVP that uses the information of motion vectors of neighboring blocks, the geometry of the camera position is utilized to calculate the parallax of different viewpoints in this algorithm and this parallax is the foundation of DVP. We jointly applied the Just-Noticeable-Difference human visual model to the DVP. After filtered using Gaussian function, the geometric DVP was obtained. Experimental results showed that the proposed method achieved significant data reduction and subjective/objective quality enhancement. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 41-49, 2015 [ABSTRACT FROM AUTHOR]

Abstract: Multi-view video coding (MVC) has been extended from H.264/AVC to improve the coding efficiency of multi-view video. This paper proposes a fast mode decision algorithm which can make an early decision on the correct mode partition to solve the issue of the enormous computational complexity. The best modes of the reference views are utilized to determine the complexity of the macroblock (MB) in the current view, the mode candidates needed to be calculated can then be obtained according to the complexity. If the complexity is low or medium, the search range can be reduced. The threshold of the rate-distortion cost for the current MB is calculated using the co-located and neighboring MBs in previously coded view and is utilized as the criterion for early termination. The motion vector difference in the reference view is applied to dynamically adjust the search range in the current MB. Experimental results prove that the proposed algorithm achieves a time saving of 81.05% for a fast TZ search and 87.85% for full search, and still maintains quality performance and bitrate. [Copyright &y& Elsevier]

Multiview video coding (MVC) has attracted great attention from industries and research institutes. MVC is used to encode stereoscopic video streams for 3D playout systems such as 3D television, digital cinema, and IP network applications. MVC is an extended version of H.264/AVC that improves the performance of multiview videos. Yet, when compared with single-view video coding, MVC consumes much more time when encoding large amounts of data. Speed-up algorithms, therefore, are essential for realizing related applications. This paper presents a fast mode decision algorithm to avoid the high computational complexity of MVC. The proposed approach aims to reduce candidate modes and make mode decision process more efficient. The minimum and maximum values of rate-distortion cost (RD cost) in the previously encoded view are used to compute a threshold for each mode in the current view. Compared with joint multiview video coding, the experimental results demonstrate that the proposed algorithm provides an average of 79% in time savings with negligible bit rate increase and peak signal-to-noise ratio decrease. [ABSTRACT FROM PUBLISHER]

Mobile communication systems provide more kinds of advanced video services. One of the most significant problems of mobile video communication is to adapt video content to different network characteristics, which is critical to acceptable visual quality of the transmitted videos. This paper proposes a frame selection scheme for temporal video transcoding through frame complexity analysis that consists of visual complexity and temporal coherence. Visual complexity represents the importance of frames and temporal coherence reveals the consequences of frame skipping; both of these two features are good indicators to determine if a frame should be kept. Experimental results show that our proposed method achieves higher visual quality and has more encoded frames than other existing schemes in the same bitrate, which means that our proposed method achieves high accuracy in selecting the representative frames for temporal video transcoding. The proposed method also has better video quality assessment scores than that of other existing methods, which means the proposed method keeps higher level of integrity of the transcoded videos. [ABSTRACT FROM PUBLISHER]

The state-of-the-art video coding standard H.264 provides efficient compression and rate control for various video applications. However, by using the current rate control mechanism of H.264 for a video streaming, the output end users would experience a serious video distortion when a data burst happens in the input video. In order to ensure the output video quality and maintain a stable output bit stream, a new adaptive bit-allocation scheme is proposed in this paper. To be compatible with the widely used H.264, our adaptive bit allocation scheme incorporates a set of new allocation criteria in the rate control mechanism of H.264. Experimental results show that the proposed adaptive bit allocation scheme could produce a more stable output stream given a bursty video input stream. [ABSTRACT FROM PUBLISHER]

High Efficiency Video Coding (HEVC/H.265) is the latest international video coding standard, which achieves better compression ratio and supports higher resolution than Advanced Video Coding (H.264/AVC). However, HEVC/H.265 increases the computational burden. To reduce the coding complexity of the HEVC encoder, this paper proposes a fast inter-prediction algorithm to speed up coding time. We collect the average rate-distortion costs (RD-cost) of Skip modes and Merge modes to accelerate prediction unit (PU) mode decisions. In addition, we also acquire and analyze the motion vector range from Merge modes and Inter 2N × 2N modes to decide whether to execute Merge and advanced motion vector prediction (AMVP) of other PUs. The experimental results show that the proposed algorithm provides 48.54% time saving on average in random-access configuration and maintains good rate-distortion performance and video quality at the same time. The proposed algorithm also outperforms previous works. [ABSTRACT FROM AUTHOR]

In response to the increased demand for high-resolution video, the new generation of video standards, High Efficiency Video Coding (HEVC) and its scalable extension (SHVC) have been finalized. The compression of HEVC/SHVC is efficiently improved and supports ultra-high resolution (UHD). Therefore, the coding complexity of HEVC/SHVC is much higher than those of previous standards. The framework of SHVC is based on HEVC and is divided into several types of scalable video. SHVC can be decoded into various video resolutions, frame rates and qualities, and only needs to be encoded once, but with higher complexity than HEVC. Thus, how to reduce the coding complexity of SHVC is the purpose of this paper. Our proposed algorithm accelerates the enhancement layer (EL) prediction by utilizing encoded Coding Unit (CU) sizes, prediction modes, motion vectors and Rate-Distortion Costs (RD-Costs) of the base layer (BL) and encoded CU sizes of the enhancement layer for quality scalability of SHVC. Experimental results show that the proposed algorithm can save lots of time while maintaining good video quality, and the performance is better than those of previous works. [ABSTRACT FROM AUTHOR]

To benefit network transmission, the bit stream of the whole frame coded by H.264 is usually grouped into a single packet. However, the error and packet loss during the transmission will result in the distortion of reconstructed video. To deal with this problem, error concealment is widely used to recover the lost frames and to prevent error propagation. In this paper, we propose an accurate motion vector refinement algorithm to further refine the well-known motion copy error concealment method and thus improve the concealed results. By using the motion vector correlation from spatial and temporal domains, a possible motion vector difference variation area has been discovered by the recursive motion vector difference examining approach in the previous frame. Afterwards, a more precise motion vector difference can be derived from the selected motion vector difference variation area. Through the help of our proposed algorithm, the refined motion vectors can be obtained and thus improve the accuracy of motion vectors derived by a motion copy error concealment algorithm. Simulation results show that our proposed algorithm can achieve better performance compared to well-known schemes. [ABSTRACT FROM PUBLISHER]

Highlights • Novel unit prediction method for efficient HEVC-to-SHVC transcoding is proposed. • Two proposed techniques are early termination and adaptive confidence interval. • We are among the first to propose a fast HEVC-to-SHVC transcoding framework. • Proposed method reduces encoding time of SHVC by 74.14% almost without quality loss. To support good video quality of experiences in heterogeneous environments, transcoding an existed HEVC (high efficiency video coding) video bitstream to a SHVC (scalability extension of HEVC) bitstream with quality scalability is highly required. A straightforward way is to first fully decode the input HEVC bitstream and then fully re-encode it with the SHVC encoder, which requires a tremendous computational complexity. To solve the problem, in this paper, a coding unit complexity (CUC)-based prediction method for predictions of CU (coding unit) depth and PU (prediction unit) mode for efficient HEVC-to-SHVC transcoding with quality scalability is proposed to significantly reduce the transcoding complexity. The proposed method contains two prediction techniques, including (i) early termination and (ii) adaptive confidence interval, and predicts the CU depth and PU mode relying on the decoded information from the input HEVC bitstream. Experimental results have shown that the proposed method significantly outperforms the traditional HEVC-to-SHVC method by 74.14% on average in reductions of encoding time for SHVC enhancement layer. [ABSTRACT FROM AUTHOR]