Adaptive rate distortion optimisation for H.264 intra coding

Rate distortion optimisation (RDO), which is the best performing mode decision method for H.264, does not consider dependence between neighbouring blocks, because calculating rate distortion (RD) costs for all possible mode sets requires too many computations. However, in H.264 intra coding, RD performance of the current block is affected by reference pixels in neighbouring blocks. Thus, considering dependence between neighbouring blocks can enhance RD performance in mode decision. Proposed is an adaptive RDO for H.264 intra coding. To consider block dependence with only a few more computations, a mode decision criterion is proposed for I4 x 4 using the partial boundary sum of the squared differences. Experimental results show that the proposed method improves RD performance compared to RDO.     

H.264低码率视频应用的率失真模型及码率控制

提出了一种通用的率失真(RD,rate distortion)模型,进而提出纹理复杂度(TC,texture-complexity)和图像块头用字节自适应线性预测模型及宏块(组)比特分配模型。利用以上模型,构建了一种面向低码率视频应用的码率控制方案。大量仿真实验结果表明,利用新提出的码率控制方法,测试序列的峰值信噪比(PSNR)均有不同程度提高,其码流曲线和PSNR曲线更平滑平稳,目标码率控制更准确。     

Content-adaptive bitstream-layer model for coding distortion assessment of H.264/AVC networked video

Bitstream-layer models are designed to use the information extracted from both packet headers and payload for real-time and non-intrusive quality monitoring of networked video. This paper proposes a content-adaptive bitstream-layer (CABL) model for coding distortion assessment of H.264/AVC networked video. Firstly, the fundamental relationship between perceived coding distortion and quantization parameter (QP) is established. Then, considering the fact that the perceived coding distortion of a networked video significantly relies on both the spatial and temporal characteristics of video content, spatial and temporal complexities are incorporated in the proposed model. Assuming that the residuals before Discrete Cosine Transform (DCT) keep to the Laplace distribution, the scale parameters of the Laplace distribution are estimated utilizing QP and quantized coefficients on the basis of the Parseval theorem firstly. Then the spatial complexity is evaluated using QP and the scale parameters. Meanwhile, the temporal complexity is obtained using the weighted motion vectors (MV) considering the variations in temporal masking extent for high motion regions and low motion regions, respectively. Both the two characteristics of video content are extracted from the compressed bitstream without resorting to a complete decoding. Using content related information, the proposed model is able to adapt to different video contents. Experimental results show that the overall performance of CABL model significantly outperforms that of the P.1202.1 model and other coding distortion assessment models in terms of widely used performance criteria, including the Pearson Correlation Coefficient (PCC), the Spearman Rank Order Correlation Coefficient (SROCC), the Root-Mean-Squared Error (RMSE) and the Outlier Ratio (OR).     

基于显著特征的HEVC帧内率失真优化

引入感知因素的RDO算法和感知编码可以提高编码视频主观质量,但也产生了明显的率失真性能损失。针对上述问题,提出了一种基于显著特征的 RDO 方法。首先探索了 HEVC 编码树单元的码率分布和显著特征之间的相关性,提出显著码率先验模型并确定了模型的初始参数;然后建立了码率差异最小化的率失真代价模型,并根据该模型推导得到自适应拉格朗日乘子计算方法;最后设计了模型参数更新规则。实验结果表明,算法在率失真性能基本不变的情况下,提高了视频的主观质量。     

H.264帧间预测编码块匹配模式的研究

H.264是一种适应于低码率传输的新一代视频压缩标准,在其编码技术中,运动估计是提高编码效率的关键。通过分析H.264编码过程,针对多模式的块匹配运动估计计算量巨大这一问题提出改进措施,并应用软件进行实验仿真。结果表明:在保证图像质量的情况下,降低了运算的复杂度,提高编码效率。     

SSIM-based error-resilient rate-distortion optimization of H.264/AVC video coding for wireless streaming

The SSIM-based rate-distortion optimization (RDO) has been verified to be an effective tool for H.264/AVC to promote the perceptual video coding performance. However, the current SSIM-based RDO is not efficient for improving the perceptual quality of the video streaming application over the error-prone network, because it does not consider the transmission induced distortion in the encoding process. In this paper, a SSIM-based error-resilient RDO scheme for H.264/AVC is proposed to improve the wireless video streaming performance. Firstly, with the help of the SSE-based RDO, we present a low-complexity Lagrange multiplier decision method for the SSIM-based RDO video coding in the error-free environment. Then, the SSIM-based decoding distortion of the user end is estimated at the encoder and is correspondingly introduced into the RDO to involve the transmission induced distortion into the encoding process. Further, the Lagrange multiplier is theoretically derived to optimize the encoding mode selection in the error-resilient RDO process. Experimental results show that the proposed SSIM-based error-resilient RDO can obtain superior perceptual video quality (more structural information) to the traditional SSE-based error-resilient RDO for wireless video streaming at the same bit rate condition.     

Direction-adaptive fixed length discrete cosine transform framework for efficient H.264/AVC video coding

The 2D-discrete cosine transform (2D-DCT) is one of the popular transformation for video coding. Yet, 2D-DCT may not be able to efficiently represent video data with fewer coefficients for oblique featured blocks. To further improve the compression gain for such oblique featured video data, this paper presents a directional transform framework based on direction-adaptive fixed length discrete cosine transform (DAFL-DCT) for intra-, and inter-frame. The proposed framework selects the best suitable transform mode from eight proposed directional transform modes for each block, and modified zigzag scanning pattern rearranges these transformed coefficients into a 1D-array, suitable for entropy encoding. The proposed scheme is analysed on JM 18.6 of H.264/AVC platform. Performance comparisons have been made with respect to rate-distortion (RD), Bjontegaard metrics, encoding time etc. The proposed transform scheme outperforms the conventional 2D-DCT and other state-of-art techniques in terms of compression gain and subjective quality.     

Efficient entropy coding scheme for H.264/AVC lossless video coding

Context-based adaptive variable length coding (CAVLC) and context-based adaptive binary arithmetic coding (CABAC) are entropy coding methods employed in the H.264/AVC standard. Since these entropy coders are originally designed for encoding residual data, which are zigzag scanned and quantized transform coefficients, they cannot provide adequate coding performance for lossless video coding where residual data are not quantized transform coefficients, but the differential pixel values between the original and predicted pixel values. Therefore, considering the statistical characteristics of residual data in lossless video coding, we newly design each entropy coding method based on the conventional entropy coders in H.264/AVC. From the experimental result, we have verified that the proposed method provides not only positive bit-saving of 8% but also reduced computational complexity compared to the current H.264/AVC lossless coding mode.     

Requantization transcoding for H.264/AVC video coding

In this paper, efficient solutions for requantization transcoding in H.264/AVC are presented. By requantizing residual coefficients in the bitstream, different error components can appear in the transcoded video stream. Firstly, a requantization error is present due to successive quantization in encoder and transcoder. In addition to the requantization error, the loss of information caused by coarser quantization will propagate due to dependencies in the bitstream. Because of the use of intra prediction and motion-compensated prediction in H.264/AVC, both spatial and temporal drift propagation arise in transcoded H.264/AVC video streams. The spatial drift in intra-predicted blocks results from mismatches in the surrounding prediction pixels as a consequence of requantization. In this paper, both spatial and temporal drift components are analyzed. As is shown, spatial drift has a determining impact on the visual quality of transcoded video streams in H.264/AVC. In particular, this type of drift results in serious distortion and disturbing artifacts in the transcoded video stream. In order to avoid the spatially propagating distortion, we introduce transcoding architectures based on spatial compensation techniques. By combining the individual temporal and spatial compensation approaches and applying different techniques based on the picture and/or macroblock type, overall architectures are obtained that provide a trade-off between computational complexity and rate-distortion performance. The complexity of the presented architectures is significantly reduced when compared to cascaded decoder–encoder solutions, which are typically used for H.264/AVC transcoding. The reduction in complexity is particularly large for the solution which uses spatial compensation only. When compared to traditional solutions without spatial compensation, both visual and objective quality results are highly improved.     

H.264码率控制算法分析

首先对固定码率控制和可变码率控制进行了介绍,然后结合H.264/AVC对码率控制的特殊要求,对目前有代表性的H.264码率控制算法进行了综合评述,指出其优缺点.     

基于SSIM的HEVC帧内编码率失真优化

率失真优化(RDO)是视频编码压缩中的关键技术之 一。传统的率失真优 化技术使用误差平方和(SSE)或绝对差和(SAD)度量失真, 不能获得较好的视觉感知质量。本文针对新一代视频编码标准高效视频编码(H EVC)帧内编码RDO,提出了一种基于结构相似度(SSIM)度量失真的 RDO方法。首先,根据HEVC编码树形单元(CTU)结构设计了基于SSIM的失真计算方法; 然后,提出了一种基于量化器推导的码率-量化步长(R-Δ)模型和一种基于统计分析的失 真 -量化参数(DSSIM-QP)模型,用于求取拉格朗日乘数;最终,使用多QP优化方法求 取模 型参数。实验表明,相对于HEVC 传统的RDO,针对全I帧(即所有帧都为帧内编码)固定QP编码和多QP优化编 码,在相同的SSIM条 件下,码率分别平均降低8.4%和13.9%左右,同时编码复杂度分别平均增加约3%和2%。     

H.264解码器的设计与优化

介绍了一种H.264(JVT)解码器的软件设计及其优化方法。以H.264测试模型jm50c为参考重新设计H.264解码器，为解码器的设计及优化提供了一种方法。试验结果表明，本方法与jm50c相比，解码速度提高了10-25倍。     

一种新的H.264/AVC帧内编码快速算法

针对H.264/AVC帧内编码算法采用率失真优化(RDO)算法提升编码性能导致运算复杂度增加这一问题,提出了一种新的帧内编码快速算法。该算法采用待预测块的纹理方向误差值判断待编码块的纹理特征,结合相邻块的预测模式相关性减少须遍历预测模式的数量,并结合全零块检测的提前终止判定准则加快编码速度。实验结果表明,与标准算法相比,该算法在保证输出码率和图像质量基本不变的情况下能够将帧内编码时间减少约67.2%,显著提高了H.264的帧内编码效率。     

H.264编码环中的去块效应滤波系统

介绍了H.264的编解码模型系统中的去块效应滤波系统，分析了该系统原理及其相对于以往去块效应滤波系统的改进。并通过仿真实验验证了该系统在提高图像质量和降低视频流码率上的较好作用。     

一种H.264基本单元层的码率控制算法

在基本单元层上提出利用峰值信噪比(PSNR)和平均绝对差(MAD)联合估计编码复杂度,并加入了基本单元的位置权值来使目标比特更加精确.由于MAD的线性模型计算复杂度较高,考虑到MAD的时间和空间相关性,本文采用了MAD的加权模型,省略了MAD线性模型的参数更新过程,降低了编码复杂度.试验结果表明:与JM8.6采用的JVT-H017算法相比,本文算法码率精度更高,输出码流更加平稳,图像质量更好.     

基于H.264的码率控制算法研究与改进

码率控制作为H.264中的关键技术,在参考软件Joint Model(JM)中已给出其算法.由于JM算法采用线性模型预测MAD,运算量较大且存在一定的误差,为此提出了新的加权预测模型,同时在原算法基础上增加了宏块层码率控制策略.仿真结果显示,采用改进算法的H.264编码器在取得更低比特率的同时还有效提高了PSNR.     

一种改进的H.264码率控制算法

码率控制是H.264视频编码中一项重要技术,对平稳码率和保证良好的图像质量起着重要作用.通过分析H.264 JVT-012中目标码率计算与分配算法的缺陷,提出了基于图像直方图和滑动窗技术的自适应改进方法.根据图像复杂度和场景切换,通过图像直方图和滑动窗引入比率因子λ,对预测的MAD进行自适应调整,使之更加接近真实的MAD值,从而有效地提高了码率控制的性能.实验结果表明,与JVT-G012算法相比,目标码率匹配更精确,图像解码质量提高且PSNR变化较小,并能较好地处理场景切换等问题.