基于HEVC与聚类算法的计算机桌面图像压缩算法

对基于HEVC与聚类算法的计算机桌面图像压缩方案进行研究,将计算机桌面图像进行自适应块分类,利用颜色聚类算法对块进行颜色聚类,简化颜色总类、节省码流、改善编码性能。再利用HEVC帧内预测编码算法对块进行压缩,为高清分辨率计算机桌面图像网络共享,提供高效的图像压缩方法。     

Fast CU size decision and mode decision algorithm for intra prediction in HEVC

In the intra prediction process, High Efficiency Video Coding (HEVC) provides a quadtree-based coding unit (CU) block partitioning structure and up to 35 kinds of prediction modes to improve the coding performance. These technologies improve the coding efficiency significantly while the coding complexity is simultaneously increased rapidly as well. In this paper, a novel fast CU size decision and mode decision algorithm is proposed for the intra prediction of HEVC. The overall algorithm consists of two processes, the fast CU size decision and fast mode decision. In the fast CU size decision process, we adopt an adaptive discretization total variation (DTV) threshold-based CU size determination algorithm to skip some specific depth levels. In the fast mode decision process, an orientation gradient-based mode decision is proposed to reduce the candidate modes involved in the rough mode decision (RMD) and the rate distortion optimization (RDO) process. The experimental results on the HEVC reference software HM demonstrate that the proposed algorithm can significantly reduce the coding time with negligible performance loss.     

HEVC-based lossless intra coding for efficient still image compression

Latest advancements in capture and display technologies demand better compression techniques for the storage and transmission of still images and video. High efficiency video coding (HEVC) is the latest video compression standard developed by the joint collaborative team on video coding (JCTVC) with this objective. Although the main design goal of HEVC is the compression of high resolution video, its performance in still image compression is at par with state-of-the-art still image compression standards. This work explores the possibility of incorporating the efficient intra prediction techniques employed in HEVC into the compression of high resolution still images. In the lossless coding mode of HEVC, sample- based angular intra prediction (SAP) methods have shown better prediction accuracy compared to the conventional block-based prediction (BP). In this paper, we propose an improved sample-based angular intra prediction (ISAP), which enhances the accuracy of the highly crucial intra prediction within HEVC. The experimental results show that ISAP in lossless compression of still images outclasses archival tools, state-of-the-art image compression standards and other HEVC-based lossless image compression codecs.     

基于纹理特性与空域相关的高效视频编码帧内分级快速算法

为了降低高效视频编码(HEVC)标准的编码复杂度,提出一种基于纹理特性与空域相关性的帧内分级快速算法。首先,采用最大编码单元(LCU)级的快速算法,通过利用相邻LCU的编码深度值加权预测得到当前LCU的预测深度,并利用块标准差和自适应阈值策略确定当前LCU的纹理复杂度,将当前LCU的预测深度和纹理复杂度相结合来预测当前LCU的最有可能深度范围(MPDR);其次,采用编码单元(CU)级的深度判决快速算法(CUDD-FA),将基于边缘图的CU深度预判策略和基于率失真(RD)代价相关性的CU提前中止策略相结合,实现了CU级深度的提前确定,进一步降低了帧内编码复杂度。与原始HEVC算法相比,所提算法在全I帧编码模式下编码时间平均减少41.81%,BD-rate(Bjøntegaard Delta bit rate)仅上升0.74%,BDPSNR(Bjøntegaard Delta Peak Signal-to-Noise Rate)仅降低0.038 dB;与代表性文献算法相比,所提算法在编码时间节省更多的情况下率失真性能更好。实验结果表明,在率失真性能损失可以忽略不计的前提下,所提算法能有效降低HEVC帧内编码复杂度,特别是高分辨率视频序列,有利于HEVC的实时视频应用。     

An AR based fast mode decision for H.265/HEVC intra coding

As a critical technique to raise coding efficiency in H.265/HEVC (H.265/High Efficiency Video Coding), the number of prediction modes for intra coding is much larger than that in H.264/AVC. However, the large number of prediction modes also leads to high complexity. In this paper, an AR (Auto Regression) based fast mode decision method for H.265/HEVC intra coding is proposed, including an AR based fast mode selection and an MPM (Most Probable Mode) joint fast mode selection method. Considering the correlation between SATD (Sum of Absolute Transformed Differences) cost and RD (Rate-Distortion) cost, we establish a selective function controlled by an adaptive parameter which is acquired by an AR model. According to the distribution of the SATD cost, the selective function can decide which modes can be discarded and which modes can be used for the FMD (Fine Mode Decision). In addition, in order to further reduce the number of candidate modes for FMD, an MPM joint fast mode selection method is presented based on the relationship between MPMs and candidate modes. Experimental results show that just in PU layer, the proposed AR based fast intra mode decision method can save encoding time by 32 % with negligible coding loss in all-intra main configuration compared to the intra mode decision of HM13.0.     

Fast HEVC I-frame coding based on strength of dominant direction of CUs

High efficiency video coding (HEVC), the latest international video coding standard, greatly outperforms previous standards such as H.264/AVC in terms of coding bitrate and video quality. The coding efficiency improvement in HEVC is achieved by introducing several new techniques such as recursive quad-tree structure and increased number of intra prediction modes. However, computational load is also increased due to employing the new techniques. In this paper, we propose a solution for fast I-frame coding in HEVC standard using homogeneity of Coding Units (CUs). The proposed solution consists of two stages. In the first stage, we evaluate CU homogeneity by computing a parameter named dominant direction strength and predict CU size by this means. In the second stage, we select 11 modes out of 35 for the specified CU size based on dominant direction of the CU. Experimental results indicate that the proposed method achieves on average 45.8 % reduction on coding time, with very similar coding efficiency as the HEVC reference software. Moreover, we designed tree-stage pipelined architecture for our method which can operate at 235 MHz maximum clock rate which means it can be used for real-time coding of all intra configuration of HEVC videos up to level 6.2.     

HEVC快速帧内模式决策算法

在高效视频编码(HEVC)标准中,为降低编码单元和预测单元算法的计算复杂度,提出一种基于编码单元纹理和预测单元模式决策的快速帧内预测算法。通过统计编码单元的纹理复杂度,分析编码单元纹理的相关性,设定合理的纹理阈值,快速地决策当前编码单元的大小。改进预测单元模式决策算法,利用三步搜索方法,减少候选模式数量和帧内模式预测时间。算法结合了编码单元和预测单元的特点,仿真结果表明,与HEVC参考软件HM8.0相比,在增加较少码率,降低较少峰值信噪比的情况下,该算法的编码时间平均缩减40.9%,降低了编码复杂度。     

基于颜色聚类的计算机桌面图像压缩算法

针对计算机桌面图像压缩问题,提出一种基于颜色聚类的图像压缩算法。将桌面图像划分成16×16的非重叠块,归为文本/图形块、自然图像块及混合块3类。对色彩丰富文本/图形块进行颜色聚类,以降低块的颜色种类数,并做无损压缩。对自然图像块采用H.264帧内预测编码方法,对混合块采用混合编码方法。实验结果表明,该算法所得图像的峰值信噪比和结构相似度均高于传统算法。     

一种HEVC帧内预测模式快速选择算法

针对HEVC帧内预测模式选择过程计算较为复杂的问题,提出了一种帧内预测模式快速选择算法。在统计实验数据的基础上,针对64[×]64、32[×]32、16[×]16较大尺寸的预测单元类型,采用阈值法筛选掉粗选后可能性较小的预测模式,针对8[×]8、4[×]4较小尺寸的预测单元类型,根据代价值的分布情况,直接筛减或者采用模式梯度直方图法筛选掉粗选后可能性较小的预测模式,从而减少最后进行率失真代价精密计算的帧内预测模式数量,降低帧内编码复杂度。实验结果表明,在保证图像质量和编码码率的情况下,该算法能有效提高HEVC的编码速度,有利于实时应用。     

面向CPU-GPU平台的HEVC编码器优化

针对CPU-GPU平台提供了一种能显著降低高效视频编码(high efficiency video coding,简称HEVC)复杂度的优化方案.根据编码器的复杂度分布及不同模块的特点,针对帧内预测、帧间预测以及环路滤波分别进行了优化.在帧内预测中,基于相邻编码单元(coding unit,简称CU)之间的相关性,提出了一种CU的深度决策方法以及一种减少率失真优化(RDO)的模式数量的方法,降低了帧内编码的复杂度.在帧间预测中,提出将耗时最大的运动估计模块完善在图形处理单元(GPU)上,通过中央处理单元(CPU)和GPU的流水线工作获得了明显的加速,并基于预测残差的能量提出了一种编码单元提前终止划分的方法,有效降低了帧间编码复杂度.在环路滤波中,提出了一种GPU端的自适应样本点补偿(sample adaptive offset,简称SAO)参数决策方法及去块滤波方法,有效分担了CPU端的复杂度.上述优化实现在HM16.2上,实验结果表明,提出的优化方案可以获得高达68%的编码复杂度节省,而平均性能损失仅为0.5%.     

高效率视频编码快速帧内预测算法

针对高效率视频编码(HEVC)帧内预测过程中,编码单元四叉树划分算法计算复杂度极高的问题,提出一种基于多重纹理特征的HEVC帧内编码单元快速划分算法,该算法能够缩小划分的深度区间。首先,使用自定义的纹理提取方法提取出编码单元中的多重纹理特征;其次,使用支持向量机(SVM)对多重纹理特征参数进行训练,得出决策函数;最后,根据决策函数,跳过前面不必要的划分和提前终止划分。实验结果表明,同原始HM 12.0相比,快速划分算法编码时间平均减少43.23%,码率平均增加0.84%,明显提高了帧内编码效率。此外,所提算法容易与其他算法进行融合,进一步降低HEVC的帧内计算复杂度。     

一种基于距离加权帧内预测的纹理块划分方法

提出了一种基于距离加权帧内预测的纹理块划分方法。这种帧内预测的方法能很好地描述纹理的方向,可以为方向变换编码和图像检索等应用提供准确的边信息。实验表明,该方法能准确地采用较大的块来描述纹理简单的图像区域,采用较小的块来描述纹理复杂的区域,且很好地反映了预测方向和纹理方向之间的一致性。     

A computationally scalable fast intra coding scheme for HEVC video encoder

Multimedia Tools and Applications - The High Efficiency Video Coding (HEVC) adopts 35 intra prediction modes to provide a more precise intra prediction. As a result, HEVC intra coding is much more...     

A low energy intra prediction hardware for high efficiency video coding

Intra prediction algorithm in the recently developed high efficiency video coding (HEVC) standard has very high computational complexity. Therefore, in this paper, we propose pixel equality and pixel similarity based techniques for reducing amount of computations performed by HEVC intra prediction algorithm and, therefore, reducing energy consumption of HEVC intra prediction hardware. The proposed techniques significantly reduce the amount of computations performed by 4 × 4 and 8 × 8 luminance angular prediction modes with a small comparison overhead. Pixel equality based technique does not affect the PSNR and bit rate. Pixel similarity based technique increases the PSNR slightly for some video frames and it decreases the PSNR slightly for some video frames. We also designed and implemented a low energy HEVC intra prediction hardware for 4 × 4 and 8 × 8 angular prediction modes including the proposed techniques using Verilog HDL. The proposed techniques significantly reduce the energy consumption of this HEVC intra prediction hardware.     

H．264帧内方向预测的研究

在H．264视频编解码标准中,帧内4×4亮度块的预测模式有9种。在对这些预测模式的预测能力进行分析后．发现在不同帧内预测模式预测能力存在差异。为了解决这一问题,提出了一种更改编解码次序的方法对预测能力较差的模式进行编解码。实验结果表明该方法可以使预测能力较差的模式的预测能力得到改善．     

HEVC optimization based on human perception for real-time environments

High-Efficiency Video Coding (HEVC) is the new emerging video coding standard of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). The HEVC standard provides a significant improvement in compression efficiency in comparison with existing standards such as H264/AVC by means of greater complexity. In this paper we will examine several HEVC optimizations based on image analysis to reduce its huge CPU, resource and memory expensive encoding process. The proposed algorithms optimize the HEVC quad-tree partitioning procedure, intra/inter prediction and mode decision by means of H264-based methods and spatial and temporal homogeneity analysis which is directly applied to the original video. The validation process of these approaches was conducted by taking into account the human visual system (HVS). The adopted solution makes it possible to perform HEVC real time encoding for HD sequences on a low cost processor with negligible quality loss. Moreover, the frames pre-processing leverages the logic units and embedded hardware available on an Intel GPU, so the execution time of these stages are negligible for the encoding processor.

     

H.264帧内预测快速模式选择

H.264/AVC视频编码标准中用率失真优化(RDO)方法为一个宏块(MB)判决最佳编码模式来提高编码效果,加大了算法复杂度并且计算冗余大。为了克服这一缺点,一种快速帧内预测模式选择算法被提出。在色度预测中,根据宏块的色度纹理复杂度,把原先的4种模式降到1或2种;在亮度16×16块模式判决中,根据最小哈达玛变换的绝对误差和(SATD)来选择最佳模式;在亮度4×4块模式判决中,该算法在9种模式中选择3种可能模式作为候选模式。通过比较16个4×4块总代价与1个16×16块的代价来选择最佳块选择模式,实验表明,该算法能在节省69%左右编码时间的情况下,比特率与峰值信噪比(PSNR)保持不变。     

基于梯度的H.265/HEVC帧内预测硬件加速算法研究

HEVC即H.265,是目前最新的视频编码标准。相比于前一代视频编码标准,H.265/HEVC虽然能够明显改善视频压缩效率,但是却带来了更高的计算复杂度,尤其是在帧内预测过程中。为了解决这个问题,提出一种基于梯度的帧内预测硬件加速算法来跳过一些帧内预测模式和划分深度的预测过程,从而达到减少计算的目的。利用图像梯度信息来粗略估计编码单元的纹理方向和纹理复杂度,其中纹理方向用来估计编码单元的最优帧内预测方向,纹理复杂度用来判断是否跳过当前划分深度的预测编码过程。实验表明,相比于H.265/HEVC测试模型HM16.18,本文提出的算法能够减少6059%的编码时间,仅造成0.38 dB的BD PSNR减少和8.52%的BD-Rate增加。     

利用纹理和空间相关性的HEVC帧内预测模式选择

目的 提出一种结合图像纹理方向和空间相关性的高效视频编码（HEVC）帧内模式选择快速算法,减少粗模式选择过程的候选模式数目,加快帧内模式选择速度。方法 首先,使用Sobel算子获得当前预测单元（PU）的纹理方向,利用此纹理方向选取相应的角度预测模式组成粗模式选择的候选模式列表;另外,利用图像的空间相关性,将相邻预测单元的最优帧内预测模式添加到候选模式列表中。结果 本文算法将粗模式选择过程的候选模式数目从35种减少到不超过10种,比特率升高0.41%,峰值信噪比下降0.0314 dB,编码时间缩短了34.9%。结论 实验结果显示,在保持编码质量基本不变的情况下,此算法明显减少了粗模式选择过程的预测模式数量,提高了HEVC的编码效率。     

基于全零模块检测的H.264/AVC快速帧内模式选择算法*

H.264/AVC采用多方向、多划分的帧内预测模式,与其他视频编码标准相比具有更高的编码效率,但同时也使计算复杂度明显提升。通过分析各编码模式的特点和最佳模式分布规律,提出了基于全零模块检测的快速帧内模式选择算法,略过不可能进一步降低率失真代价的帧内预测模式,以降低编码过程的计算复杂度。实验结果表明,在保证编码性能的前提下,可以有效地降低H.264/AVC的计算复杂度。