Piecewise DC prediction in HEVC

In this paper, we propose an improved DC prediction method for high-efficiency video coding (HEVC) intra coding. The technique involves the application of pixel-wise predictors rather than block-based predictor in the DC mode. In HEVC, the pixels of neighboring reconstructed blocks are used to support multiple directional spatial prediction modes and reduce spatial redundancy. For lossless coding, pixel-by-pixel differential pulse code modulation (DPCM) is applied to directional predictions. Consequently, residuals are reduced and coding efficiency is improved. Since DC prediction still employs block-based coding, pixel-wise DC prediction is needed for better coding efficiency. When compared to HEVC lossless intra coding, the proposed algorithm reduces the bit rate by 5.95%. Furthermore, with pixel-by-pixel DPCM, the average bit rate reduction is 10.64% when compared to HEVC lossless intra coding.     

基于邻近值的HEVC帧内预测优化

高性能视频编码(High Efficiency Video Coding,HEVC)标准中的帧内编码模式利用当前帧中像素点之间的空间相关性作出有效预测。为了解决待编码像素远离参考像素时预测不准确的问题,提出了一种基于邻近值的HEVC帧内预测优化算法。该算法的主要思想是,对于当前像素,先根据传统HEVC帧内编码方法得到其预测值,再使用该像素点左边、左上、上边位置的修正值以及该像素本身的预测值对该预测值进行修正。因为将当前像素与周围像素的相关性进行了有效的数学建模,所以HEVC帧内编码性能得到了提升。实验结果显示,所提算法与HEVC标准相比,最高节省了2.7%的码率,平均节省的码率为1.3%。     

Improved lossless intra coding for H.264/MPEG-4 AVC.

A new lossless intra coding method based on sample-by-sample differential pulse code modulation (DPCM) is presented as an enhancement of the H.264/MPEG-4 AVC standard. The H.264/AVC design includes a multidirectional spatial prediction method to reduce spatial redundancy by using neighboring samples as a prediction for the samples in a block of data to be encoded. In the new lossless intra coding method, the spatial prediction is performed based on samplewise DPCM instead of in the block-based manner used in the current H.264/AVC standard, while the block structure is retained for the residual difference entropy coding process. We show that the new method, based on samplewise DPCM, does not have a major complexity penalty, despite its apparent pipeline dependencies. Experiments show that the new lossless intra coding method reduces the bit rate by approximately 12% in comparison with the lossless intra coding method previously included in the H.264/AVC standard. As a result, the new method is currently being adopted into the H.264/AVC standard in a new enhancement project.     

一种新的用于屏幕图像编码的HEVC帧内模式

由于传统编码方式对屏幕图像的编码效果不佳,该文根据屏幕图像包含大量非连续色调内容的特点,在HEVC(High Efficiency Video Coding)基础上,提出一种新的帧内编码模式称为帧内串匹配(Intra String Copy, ISC)。基本思想是在HEVC的编码单元(Coding Unit, CU)级别上,引入字典编码工具:编码时,在一定长度的字典窗口内,利用散列表,对当前CU内的像素,进行串搜索和匹配;解码时,根据像素串匹配的距离和匹配长度,在重建缓存内复制相应位置像素重建当前CU像素。实验结果表明,在编码复杂度增加很少的情况下,对于典型的屏幕图像测试序列,在全帧内(All Intra, AI),随机接入(Random Access, RA),低延迟(Low-delay B, LB)3种配置下,有损编码模式比HEVC分别节省码率15.1%, 12.0%, 8.3%,无损编码模式分别节省码率23.3%, 14.9%, 11.6%。     

基于残差偏置和查找表的高光谱图像无损压缩

为了提高高光谱遥感图像的压缩比,提出一种基于残差偏置和查找表的高光谱图像无损压缩方法。在高光谱图像的第一谱段图像采用了无损压缩标准中值预测器方法进行谱段内预测,其它谱段图像采用谱间预测方法。首先,在多级查找表（LAIS-LUT）预测方法的基础上搜索当前预测值,用当前预测值周围特定的5个像素点和当前像素值周围相同位置的5个像素点进行比较,通过比较结果,得出一个偏置值;然后在预测残差上加上偏置值;最后,将最终预测残差进行算术编码,并进行了理论分析和实验验证。结果表明,针对美国航空航天局的高光谱图像,所提出的方法比LAIS-LUT压缩比平均提高0.05;针对国内高光谱图像,该方法比LAIS-LUT压缩比平均提高0.07。这一结果对提高高光谱图像压缩效率是有帮助的。     

An efficient intra-mode decision method for HEVC

This paper proposes a new intra-mode decision method for HEVC. The proposed method makes use of the characteristics of some special modes that belong to both rough mode decision mode set and most probable mode set. It also improves the coding efficiency by adaptively applying different algorithms depending on the prediction unit size. Not only the luma components but also the chroma components are considered in this paper. In the intra-coding process for the chroma components, the proposed method changes the examination order and makes efficient use of the spatial correlation and coded block flag information. As a result, the proposed method shows significantly better performance compared to other intra-mode decision methods.     

Fast CU size and prediction mode decision method for HEVC encoder based on spatial features

In the high-efficiency video coding (HEVC) standard, intra prediction has higher computational complexity compared with H.264/AVC (advanced video coding) because of increasing the number of intra prediction modes and also higher number of coding unit (CU) sizes. The HEVC encoder evaluates 35 prediction modes on five possible prediction unit (PU) sizes to find the one with the minimum rate–distortion cost. Although this approach improves coding efficiency, it is very time-consuming. In this paper, we propose a fast intra prediction method to reduce the complexity of I-frame coding. The proposed method consists of three stages which is based on smoothness spatial feature. In the first stage, a measure is introduced to estimate CU smoothness by using sum of absolute differences (SAD) among CU pixels in four directions. By considering that a smooth region can be predicted with larger CUs, when the measured smoothness parameter is lower than a predefined threshold, only the prediction modes in the current CU are evaluated. In the second stage, the number of intra prediction modes is reduced based on the calculated SADs in the previous stage. In the last stage, if the first three candidate modes resulted from rough mode decision stage in the previous PU and the current PU are similar, then the best mode prediction of the previous PU is selected as the best candidate mode. Experimental results indicate that the proposed method can reduce the coding time on average to 43 % and maintain coding video quality, whereas bitrate increases negligibly (0.5 %).     

Performance enhancement of HEVC lossless mode using sample-based angular and planar predictions

High-efficiency video coding (HEVC) is the state-of-the-art video compression standard designed to handle the storage and transmission requirements of next-generation multimedia services. In the lossless mode HEVC, prevailing sample-based prediction algorithms in the literature have shown better prediction accuracy compared to the conventional block-based prediction within the HEVC anchor. This work proposes a sample-based prediction technique to modify the planar prediction mode of HEVC and a complete sample-based predictive encoder for the lossless mode of HEVC. In this work, we propose gradient adaptive sample-based intraprediction (GASP) as a replacement for the block-based planar prediction in HEVC. To obtain the benefits of sample-based prediction methods in both angular and planar prediction modes, we also propose a combination of ISAP, a sample-based angular prediction in the literature, with the newly proposed GASP (CIG). The experimental results demonstrate the superiority of GASP and CIG over other state-of-the-art sample-based prediction strategies in angular and planar prediction modes.     

Gradient-oriented directional predictor for HEVC planar and angular intra prediction modes to enhance lossless compression

Recent advancements in the capture and display technologies motivated the ITU-T Video Coding Experts Group and ISO/IEC Moving Picture Experts Group to jointly develop the High-Efficiency Video Coding (HEVC), a state-of-the-art video coding standard for efficient compression. The compression applications that essentially require lossless compression scenarios include medical imaging, video analytics, video surveillance, video streaming etc., where the content reconstruction should be flawless. In the proposed work, we present a gradient-oriented directional prediction (GDP) strategy at the pixel level to enhance the compression efficiency of the conventional block-based planar and angular intra prediction in the HEVC lossless mode. The detailed experimental analysis demonstrates that the proposed method outperforms the lossless mode of HEVC anchor in terms of bit-rate savings by 8.29%, 1.65%, 1.94% and 2.21% for Main-AI, LD, LDP and RA configurations respectively, without impairing the computational complexity. The experimental results also illustrates that the proposed predictor performs superior to the existing state-of-the-art techniques in the literature.     

Low-Complexity Intra-Coding Scheme for HEVC

Compared with H.264/AVC, the latest video standard High Efficiency Video Coding (HEVC) known as H.265 improves the coding efficiency by adopting the quadtree splitting structure which is flexible in representing various textural and structural information in images. However, the computational complexity is dramatically increased, especially in the intra-mode decision process owing to supporting more partitions and modes. In this paper, we propose a low-complexity algorithm for HEVC intra-coding, which consists of a fast coding unit (CU) size decision (FCUSD) method and a fast prediction unit (PU) mode decision (FPUMD) method. In FCUSD, unnecessary CU sizes are skipped early according to the depth level of neighboring CUs and the rate distortion (RD) cost threshold derived from the former coded frame. In FPUMD, the PU mode and RD cost correlations between different depth levels are utilized to terminate unnecessary candidate modes. Experimental results demonstrate that the proposed algorithm can achieve about 50.99 % computational complexity reduction on average with 1.18 % BD-rate increase and 0.08 dB BD-psnr loss.     

Improved SAP based on adaptive directional prediction for HEVC lossless intra prediction

In HEVC (High Efficiency Video Coding), linear interpolation of the boundary pixels is used as the predictor and pixels within the same PU (Prediction Unit) are in the same prediction direction. When the PU block is large and in high complexity, the prediction performance would worsen. Although many algorithms use the pixel-based weighted averaging or interpolation operations to perform the prediction which improves the performance of bitrate saving notably, there is still space for further improvement. This paper proposed an improved SAP (Sample-based Angular Prediction) algorithm based on adaptive directional prediction (ADSAP). The innovation of this paper lies in two aspects: it puts forward a new method to estimate the best prediction direction of current pixel and it introduces the concept of “frame-level pretreatment” which could greatly improve the encoding speed. Experimental results show that it could save the output bitrate by about 9.4158% when compared with the HEVC lossless intra prediction algorithm, which is better than other typical algorithms. Besides, the encoding and decoding time are reduced by about 11%. Moreover, when the minimum PU size gets larger, the increase of output bitrate of ADSAP is much less than that of HEVC and the conventional SAP algorithm, which makes the proposed algorithm quite suitable for the compression of high resolution videos.     

基于Node-Cell结构的HEVC帧内编码

随着视频传输和广播的发展,高分辨率视频的应用也越来越广泛,为了更好地适应高清视频内容,JCT-VC(Joint Collaborative Team on Video Coding)工作组制定了具有更高压缩效率的新一代视频压缩标准HEVC(High Efficiency Video Coding)。HEVC中的帧内预测包括Angular预测模式、planar模式等。基于Node-Cell结构的帧内预测方法在Angular预测基础上实现了双向预测,提供了更多的模式选择和更高的预测精度。Node-Cell结构中所有像素在当前块被分成两个子集,node像素点和cell像素点,node像素的重建值被用于内插预测cell像素。新增的帧内模式信息被设计为表示下采样率,它由该编码单元的细节及复杂度决定。为了保证重建质量,node像素和cell像素的残差均被发送到解码器。实验结果表明Node-Cell结构会提高预测精度。     

Cost-efficient HEVC-based quadtree splitting (HEQUS) for VVC Video Transcoding

The release of the latest video coding standard, known as Versatile Video Coding (VVC), has created the need to convert current High Efficiency Video Coding (HEVC) content to this new standard. However, the traditional cascade transcoding pipeline is not effective due to the exorbitant computational complexity of VVC. With this in mind, this paper proposes a fast HEVC-VVC transcoder that implements a probabilistic classifier based on Naïve-Bayes at the first partitioning level (128 × 128 pixels). This model uses features extracted from the 128 × 128 size blocks of the residual and reconstructed frames in the HEVC bitstream, and their correlation with the block partitioning structure. For the subsequent VVC coding depth levels, partitioning decisions are derived from the HEVC structure. The results achieve a 57.08% transcoding time reduction with a BD-rate penalty of 2.40%, compared with a traditional transcoding approach for the random access encoding configuration.     

Introduction to the High-Efficiency Video Coding Standard

The high-efficiency video coding(HEVC) standard is the newest video coding standard currently under joint development by ITU-T Video Coding Experts Group(VCEG) and ISO/IEC Moving Picture Experts Group(MPEG).HEVC is the next-generation video coding standard after H.264/AVC.The goals of the HEVC standardization effort are to double the video coding efficiency of existing H.264/AVC while supporting all the recognized potential applications,such as,video telephony,storage,broadcast,streaming,especially for large picture size video(4k × 2k).The HEVC standard will be completed as an ISO/IEC and ITU-T standard in January 2013.In February 2012,the HEVC standardization process reached its committee draft(CD) stage.The ever-improving HEVC standard has demonstrated a significant gain in coding efficiency in rate-distortion efficiency relative to the existing H.264/AVC.This paper provides an overview of the technical features of HEVC close to HEVC CD stage,covering high-level structure,coding units,prediction units,transform units,spatial signal transformation and PCM representation,intra-picture prediction,inter-picture prediction,entropy coding and in-loop filtering.The HEVC coding efficiency performances comparing with H.264/AVC are also provided.     

Efficient Inter Prediction Mode Decision Method for Fast Motion Estimation in High Efficiency Video Coding

High Efficiency Video Coding (HEVC) is the most recent video coding standard to achieve a higher coding performance than the previous H.264/AVC. In order to accomplish this improved coding performance, HEVC adopted several advanced coding tools; however, these cause heavy computational complexity. Similar to previous video coding standards, motion estimation (ME) of HEVC requires the most computational complexity; this is because ME is conducted for three inter prediction modes — namely, uniprediction in list 0, uniprediction in list 1, and biprediction. In this paper, we propose an efficient inter prediction mode (EIPM) decision method to reduce the complexity of ME. The proposed EIPM method computes the priority of all inter prediction modes and performs ME only on a selected inter prediction mode. Experimental results show that the proposed method reduces computational complexity arising from ME by up to 51.76% and achieves near similar coding performance compared to HEVC test model version 10.1.     

基于线预测及变换的帧内编码方法

提出一种以线为单位进行帧内预测编码的新方法,从预测及变换两方面提高帧内编码的性能。首先在宏块内部以水平或垂直方向的线为单位,分别参考相邻的行或列像素进行多个方向的帧内预测,减少了预测像素与参考像素间的距离,从而提高预测精度;其次,在原有的4×4离散余弦变换（DCT）基础上补充了1×16的一维DCT,并以宏块为基本单位灵...     

Mode-Dependent Templates and Scan Order for H.264/AVC-Based Intra Lossless Coding

In H.264/advanced video coding (AVC), lossless coding and lossy coding share the same entropy coding module. However, the entropy coders in the H.264/AVC standard were original designed for lossy video coding and do not yield adequate performance for lossless video coding. In this paper, we analyze the problem with the current lossless coding scheme and propose a mode-dependent template (MD-template) based method for intra lossless coding. By exploring the statistical redundancy of the prediction residual in the H.264/AVC intra prediction modes, more zero coefficients are generated. By designing a new scan order for each MD-template, the scanned coefficients sequence fits the H.264/AVC entropy coders better. A fast implementation algorithm is also designed. With little computation increase, experimental results confirm that the proposed fast algorithm achieves about 7.2% bit saving compared with the current H.264/AVC fidelity range extensions high profile.     

Fast prediction unit selection method for HEVC intra prediction based on salient regions

In order to reduce the computational complexity of the high efficiency video coding(HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit(PU) size selection method for HEVC based on salient regions is proposed in this paper. We first build a saliency map for each largest coding unit(LCU) to reduce its texture complexity. Secondly, the optimal PU size is determined via a scheme that implements an information entropy comparison among sub-blocks of saliency maps. Finally, we apply the partitioning result of saliency map on the original LCUs, obtaining the optimal partitioning result. Our algorithm can determine the PU size in advance to the angular prediction in intra coding, reducing computational complexity of HEVC. The experimental results show that our algorithm achieves a 37.9% reduction in encoding time, while producing a negligible loss in Bjontegaard delta bit rate(BDBR) of 0.62%.     

MODIS多光谱图像压缩研究

为有效存储MODIS多光谱图像数据,该文提出一种基于谱间预测和整数小波变换的多光谱图像压缩算法.首先通过构造谱间最优预测器去除谱间冗余,再利用整数小波变换和SPIHT算法对预测误差图像去除空间冗余,最后进行自适应算术编码.该方法可实现MODIS多光谱图像的无损、近无损和有损压缩,取得了满意的实验结果;在不同小波基条件下与3D-SPIHT算法比较,表明了该方法的有效性.     

基于分类和陪集码的高光谱图像无损压缩

在基于陪集码的高光谱图像压缩算法中,由于按照编码块的最大残差确定整块无损压缩所需的码率存在较大冗余,该文提出了基于分类和陪集码的高光谱图像压缩算法。首先利用前一波段对应位置的预测噪声对当前波段编码块的像素进行分类,将具有相似相关性的像素归于一类,然后对每一类像素分别进行陪集码编码。实验表明分类可以有效地降低码率。和基于陪集码的算法相比,该文算法无损压缩的平均码率降低了大约0.4 bpp。