一种低复杂度的HEVC码率控制算法

针对HEVC视频编码中帧层比特分配和率失真模型参数自适应更新,提出了一种改进的码率控制算法.该算法引入牛顿法来自适应更新率失真模型的参数;同时提出一种帧层复杂度度量方法,利用图像自身的内容特性来调整帧层比特分配;最后在编码过程中选择合适的量化参数.实验结果表明:与参考算法比较,该算法能大大降低计算复杂度,同时保持良好的码率控制性能,对含有场景突变的视频改进效果尤为明显.     

一种改进的H.264/AVC帧层码率控制算法

针对JVT-G012算法在帧层对P帧目标比特分配太过均匀,忽略了图像复杂度的问题,提出了一种简单有效的帧差比值法来进行帧层目标比特的分配,并利用缓冲区充盈度来调整当前帧量化参数的方法.通过大量实验仿真表明,与JVT-G012算法相比,该算法不仅能够更精确地控制码率,而且还提高了视频图像的质量.     

一种基于分层B帧架构的高效比特分配算法

随着分层B帧码率控制技术在SVC(可伸缩视频编码)中的广泛应用,视频编码的质量得到了很大提高,然而传统的H.264码率控制技术并未将B帧的比特分配考虑在内。提出一种基于分层B帧架构自适应调节B帧比特分配的码率控制算法,该算法研究了基于同一个图像组(GoP)中各时域层权重因子的自适应调节,为各时域层分配不同的目标比特;同时基于同一个时域层中各帧复杂度的不同,为各帧分配不同的目标比特。实验结果表明,与目前流行的分层B帧码率控制算法相比,该算法在比特控制误差并未降低的情况下,客观质量PSNR可提高0.1～0.4 dB。     

基于H.264的多参考帧快速选择算法

 H.264采用了多参考帧技术,大大提高了预测精度,改善了视频图像质量,然而这种特性同时也带来了很高的计算复杂度.为了降低H.264编码器的计算复杂度,本文提出了一种多参考帧快速选择算法.该算法充分考虑多参考帧中运动矢量的相关性以及中心偏置特性,通过对待选参考帧进行预选择,有效减少了需要进行全搜索的参考帧个数,提高了编码速度.实验结果表明,该算法在保持图像质量和码率变化很小的前提下,运动估计模块编码速度提高了30.91%.     

H.264/AVC帧内预测模式的快速选择算法

H.264/AVC帧内预测技术采用率失真优化策略进行最优化编码模式选择,提高了I帧的编码效率,但同时也提高了计算复杂度。提出了一种帧内预测模式的快速选择算法,基于亮度块的方向特性,通过一些复杂度不大的计算,选择少数几个可能性较大的预测模式进行率失真代价计算,得到最佳亮度预测模式,并以SATD计算代替率失真代价计算选择最佳色度预测模式,降低了计算复杂度,提高了编码速度。实验结果表明,提出的算法在保证图像质量的同时,编码时间平均降低了48%,而码率增加很小。     

一种H.264/AVC帧内预测模式的快速选择算法

H.264/AVC帧内预测技术采用率失真优化策略进行最优化编码模式选择,提高了I帧的编码效率,但同时也提高了计算复杂度。本文提出了一种帧内预测模式的快速选择算法,基于亮度块的方向特性,通过一些复杂度不大的计算,选择少数几个可能性较大的预测模式进行率失真代价计算,得到最佳亮度预测模式,并以 计算代替率失真代价计算选择最佳色度预测模式,降低了计算复杂度,提高了编码速度。实验结果表明,本文提出的算法在保证图像质量的同时,编码时间平均降低了48%,而码率增加很小。     

H.264图像复杂度自适应的I帧码率控制算法

该文针对H.264帧内编码码率控制(RC)效果不佳的问题,提出了一种新颖的图像复杂度自适应I帧RC算法。首先用Sobel算子检测I帧亮度像素的梯度,建立44块的边缘方向直方图,得到每个44块最可能的帧内预测模式和相应重构块,最终获得与实际编码相近的残差图像。用残差的平均绝对值表达I帧编码复杂度,并提出了一种经验型码率-量化(R-Q)模型,同时考虑缓冲区状态和序列特性为I帧分配合适的目标比特,最后为每一个图像组(GOP)得到了合适的I帧量化参数(QP)。实验结果表明,该文算法能更准确地控制I帧输出码率,有效阻止缓冲区溢出和跳帧,得到更加平稳的视频质量,序列PSNR波动减少了60%以上。     

Wyner-Ziv视频编码中无反馈速率控制算法研究

为了避免在分布式视频编码系统中使用反馈信道,提出了一种基于Wyner-Ziv编码的无反馈速率控制算法。首先,利用目标码率和目标帧率进行GOP层码率分配;然后,根据原始图像的帧间相关性动态选择量化因子和量化矩阵来分配每个GOP内关键帧和Wyner-Ziv帧的比特数;接下来,利用系数带级的相关性计算相关噪声模型参数,并选择对应的LDPC校验矩阵,提出Wyner-Ziv帧的无反馈比特面速率控制算法。实验结果表明,在给定目标码率下,所提算法的编码码率误差小于0.57%,且与现有无反馈速率控制算法相比,解码恢复图像的PSNR(峰值信噪比)可以提高1dB。另外,该算法基本没有增加编码端复杂度,可用于实际分布式视频通信系统。     

基于基本单元相关性的新型码率控制算法

在帧层和宏块层提出一种改进的码率控制算法.在帧层利用编码比特与目标比特的差值对下一帧目标比特进行调整,在宏块层利用宏块相关性提出了一种新型平均绝对差值(MAD)预测策略--大小三角形法预测宏块MAD.实验结果表明,改进算法不仅码率的控制更加精确.而且图像的视觉质量也得到提高.     

基于复杂度HEVC码率控制的算法优化

针对视频编码标准HEVC(high efficiency video coding)在编码过程中复杂度较高的帧层带宽相对不足而复杂度较低的帧层带宽相对富余之一的问题,为了降低计算复杂度,提高编码质量,本文首先通过研究复杂度在帧层编码过程中对码率分配的影响,提出了由SATD(sum of absolute transformed difference)构建复杂度模型,根据视频内容每帧的复杂程度,通过复杂度模型对帧层进行合理的比特分配。为了建立R-Q曲线,结合最大编码单元(LCU,largest coding unit)层的编码树特点,根据LCU残差信号的混合高斯分布特性进行量化参数(QP)的计算,从而使得输出码率与目标比特相等的同时尽可能提高视频质量。实验结果表明,所提出的算法比HEVC现行码率控制算法性能更加优良并且具有较强的鲁棒性,码率误差在0.01%以内,PSNR增益平均可达0.21dB。     

A locally adaptive algorithm for measuring blocking artifacts in images and videos

Block transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring image quality of a BDCT coded images or videos. It exhibits unique and useful features: (1) it examines the blocks individually so that it can measure the severity of blocking artifacts locally; (2) it is a one-pass algorithm in the sense that the image needs to be accessed only once; (3) it takes into account the blocking artifacts for high bit rate images and the flatness for the very low bit rate images; (4) the quality measure is well defined in the range of 0–10. Experiments on various still images and videos show that the new quality measure is very efficient in terms of computational complexity and memory usage, and can produce consistent blocking artifacts measurement.     

A unified rate-distortion analysis framework for transform coding: a summary

In our previous work, we have developed a rate-distortion (R-D) modeling framework H.263 video coding by introducing the new concepts of characteristic rate curves and rate curve decomposition. In this paper, we further show it is a unified R-D analysis framework for all typical image/video transform coding systems, such as EZW, SPIHT and JPEG image coding; MPEG-2, H.263, and MPEG-4 video coding. Based on this framework, a unified R-D estimation and control algorithm is proposed for all typical transform coding systems. We have also provided a theoretical justification for the unique properties of the characteristic rate curves. A linear rate regulation scheme is designed to further improve the estimation accuracy and robustness, as well as to reduce the computational complexity of the R-D estimation algorithm. Our extensive experimental results show that with the proposed algorithm, we can accurately estimate the R-D functions and robustly control the output bit rate or picture quality of the image/video encoder.     

Foveation scalable video coding with automatic fixation selection

Image and video coding is an optimization problem. A successful image and video coding algorithm delivers a good tradeoff between visual quality and other coding performance measures, such as compression, complexity, scalability, robustness, and security. In this paper, we follow two recent trends in image and video coding research. One is to incorporate human visual system (HVS) models to improve the current state-of-the-art of image and video coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. Specifically, we propose a foveation scalable video coding (FSVC) algorithm which supplies good quality-compression performance as well as effective rate scalability. The key idea is to organize the encoded bitstream to provide the best decoded video at an arbitrary bit rate in terms of foveated visual quality measurement. A foveation-based HVS model plays an important role in the algorithm. The algorithm is adaptable to different applications, such as knowledge-based video coding and video communications over time-varying, multiuser and interactive networks.     

基于自适应量化矩阵的硬判决量化算法

在视频编码中,视频量化一般分为硬判决量化(HDQ)和软判决量化(SDQ),HDQ与SDQ相比,编码性能虽有所损失,但其编码复杂度低,易于硬件实现的优点依旧是主流编码器所主要采用的量化算法.人眼具有对图像中的高频细节不敏感的特性.因此,基于Bayes最小误判概率约束,离线构建基于视频内容自适应的量化矩阵,在模拟感知SDQ算法机理下,对高频低频分量采用不同的量化步长,提高视频的主观质量和HDQ算法性能.仿真实验表明,相比于传统的HDQ算法,该文算法能达到平均5.048％的码率节省,其中WVGA和WQVGA格式平均达到10.65％的码率节省.相比于感知SDQ算法,平均码率增加仅有1.464％;算法复杂度方面,编码一帧的时间相比于感知SDQ节省了32.956％.     

A fast and low memory image coding algorithm based on lifting wavelet transform and modified SPIHT

Due to its excellent rate–distortion performance, set partitioning in hierarchical trees (SPIHT) has become the state-of-the-art algorithm for image compression. However, the algorithm does not fully provide the desired features of progressive transmission, spatial scalability and optimal visual quality, at very low bit rate coding. Furthermore, the use of three linked lists for recording the coordinates of wavelet coefficients and tree sets during the coding process becomes the bottleneck of a fast implementation of the SPIHT. In this paper, we propose a listless modified SPIHT (LMSPIHT) approach, which is a fast and low memory image coding algorithm based on the lifting wavelet transform. The LMSPIHT jointly considers the advantages of progressive transmission, spatial scalability, and incorporates human visual system (HVS) characteristics in the coding scheme; thus it outperforms the traditional SPIHT algorithm at low bit rate coding. Compared with the SPIHT algorithm, LMSPIHT provides a better compression performance and a superior perceptual performance with low coding complexity. The compression efficiency of LMSPIHT comes from three aspects. The lifting scheme lowers the number of arithmetic operations of the wavelet transform. Moreover, a significance reordering of the modified SPIHT ensures that it codes more significant information belonging to the lower frequency bands earlier in the bit stream than that of the SPIHT to better exploit the energy compaction of the wavelet coefficients. HVS characteristics are employed to improve the perceptual quality of the compressed image by placing more coding artifacts in the less visually significant regions of the image. Finally, a listless implementation structure further reduces the amount of memory and improves the speed of compression by more than 51% for a 512×512 image, as compared with that of the SPIHT algorithm.     

一种新的基于先验数据表的JPEG-LS动态码率控制算法

JPEG-LS算法简单,压缩性能出众,特别适合应用在图像的无损/近无损压缩领域。但是,无法精确控制码率的缺点使得JPEG-LS难以应用在带宽受限的卫星图像编码领域。为了解决这个问题,该文基于对JPEG-LS编码特性的分析,通过理论推导得出输出码率与失真量化参数的数学关系,提出一种以查表算法为核心的新型JPEG-LS动态码率控制算法。相对于现有的动态码率控制算法,该算法具有码率精确度高,收敛速度快等优点。     

Joint source/channel coding for multiple images

A joint source/channel coding algorithm is proposed for the transmission of multiple image sources over memoryless channels. The proposed algorithm uses a quality scalable image coder to optimally allocate a limited bit budget among all the sources to achieve the optimal overall distortion reduction for the multiple reconstructed images. In addition to the conventional un gain, it provides channel multiplexing gain, which can be much more significant. Furthermore, an extended scheme is proposed to provide flexibility between the optimization performance and complexity.     

Novel rate-distortion analysis framework for bit rate and picturequality control in DCT visual coding

The rate-distortion (R-D) behaviour of a coding system depends on both the characteristics of the input source data and the coding algorithm. The authors introduce the new concepts of characteristic rate curves and rate curve decomposition to characterise the input source data and model the coding algorithm, respectively. Based on these concepts, a novel framework for R-D analysis is developed, which serves as an alternative to the classical R-D analysis. Based on this framework, a fast algorithm is proposed to predict the R-D curve before quantisation and coding. The proposed algorithm has very low computational complexity. However, in the extensive simulations, its relative prediction error is always less than 5%, which is very small. To the best of the authors' knowledge, this is the first algorithm which is able to accurately estimate the R-D curve before quantisation and coding. With the estimated R-D curve, it is possible to accurately control the output bit rate and picture quality for transform coding of still images and video sequences. In practical visual coding applications, with the proposed R-D estimation algorithm, the coding bit rate can be accurately matched to the available network bandwidth to guarantee the successful transmission of the coded image/video data     

一种低复杂度的HEVC帧内快速编码算法

为了降低高效视频编码(HEVC)帧内编码复杂度,提出一种HEVC帧内快速编码算法。根据视频图像的纹理复杂性,提前跳过或者中止部分尺寸的编码单元(CU)的划分,减少CU深度遍历区间;同时,根据粗选过程后预测模式和代价值的统计特性采用阈值法或者梯度模式直方图法进一步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(RD)代价计算的帧内预测模式数量,进一步降低编码复杂度。实验结果表明,本文算法与HEVC原始平台相比,在全I帧编码模式下编码时间平均减少42.20%,码率(BR)上升约1.75%,峰值信噪比(PSNR)降低了0.108dB,有利于实时应用。