内容自适应的低复杂度多参考帧快速选择算法

针对移动视频业务的市场需求和移动终端设备的性能局限,提出了一种基于时空内容自适应的低复杂度多参考帧快速选择算法。在对视频序列编码模式采用率和参考帧时空相关性统计分析的基础上,根据时空相邻块最优参考帧的分布情况等信息,排除可能性较小的参考帧,缩小当前编码块的候选参考帧范围。并设定自适应的参考帧选择代价阈值,以判断是否需要扩大搜索范围。实验结果表明,该算法能大幅降低H.264的编码计算量,平均可降低49.12%的编码时间,而且基本保持编码率失真性能不损失。     

基于空域特征的H.264快速多参考帧选择算法

提出了一种H.264快速多参考帧选择算法,它利用视频序列的空间相关特性,在运动估计之前判断当前宏块的Skip编码模式,实现在运动估计过程中快速选择编码模式,基于对Skip编码模式占用概率的统计分析,设置多模式下参考帧数量.实验结果表明,本算法在PSNR损耗与全搜索算法相比不超过0.07dB的情况下,平均节约72.5%的编码时间.     

采用率失真与模式特征的多视点视频编码快速模式选择

现有的多视点视频编码使用了分层B帧（Hierarchical B Picture, HBP）的预测结构,其帧内预测、帧间预测以及视点间预测的模式选择给多视点视频编码带来了庞大的计算复杂度。针对这一问题,我们在分析了JMVC模式分布比例的基础上,提出了一个快速帧间模式选择的算法。这种算法利用率失真代价和预测模式特征之间的关系来及时判定最优模式:如果上一尺寸预测模式的率失真代价小于当前尺寸预测模式的率失真代价则认为上一预测模式为最优模式,跳过检查其他更小尺寸的预测模式;反之,如果上一尺寸的预测模式的率失真代价大于当前尺寸的预测模式的率失真代价,则继续检查其他更小的尺寸。这样,通过提前终止一些不必要的模式选择过程,多视点视频编码的计算量得到大幅的降低。实验结果表明:所提算法能在保持JMVC中全搜索算法的编码效率同时,使计算复杂度减少了81.66%。      

基于感知的多视点视频编码宏块模式选择快速算法

多视点视频编码(MVC)采取可变块模式选择技术和 多参考帧技术显著提高了编码的压缩效率,但同时带来了巨大的 编码计算复杂度。为了降低MVC的计算复杂度,提出基于感知的快速MVC宏块模式选择 算法。基于人眼视觉感知的特点,利用视觉恰可察觉失真(JND)的概念建立MVC宏块的最优模 式和JND的联系,并利用该联系确定早期结束最优宏块模式选择过程的阈值,根据当前编码 宏块的JND与阈值的 关系自适应地减少每个编码宏块的模式搜索次数,进而减少MVC的方向搜索和参考帧搜索的 次数,以降 低编码的复杂度,提高MVC速度。实验结果显示,对于不同运动特性、内容、纹理信息、相 机间距和图像 尺寸的测试序列,提出的快速算法在率失真性能几乎不变的情况下平均节约76.00% 编码时间。     

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中快速多参考帧选择算法研究

为了提高编码效率,H．264中采用了多参考帧搜索策略,其参考实现中提供了全搜索的多参考帧选择算法,这一策略的运用显然会大大增加H．264编码器的复杂度,且其复杂度的增加基本上和所使用的参考帧数戍线性增长,文中提出了一种更加快速的多参考帧选择算法,该算法可根据所得到的运动信息及编码所使用的模式信息快速确定参考帧的数量,对一些明显不可能的模式直接忽略掉了其最佳参考帧选择,其编码的性能与全搜索算法非常接近,但编码的速度却比全搜索算法快了许多。     

一种基于H.264的快速多参考帧选择算法

H．264采用的多参考帧运动估计极大地增加了编码器的复杂度。文中分析了各参考帧在运动估计中的作用,提出一种快速多参考帧选择算法以降低运算复杂度。该算法利用已编码相邻块参考帧的相关性,对参考帧进行预选择和排序,以避免不必要的运动搜索。可以与其它多参考帧运动估计算法相结合。实验结果表明,与H．264参考软件JM9．6中的快速算法UMHexagonS相比,提出的算法在保持编码图像质量的同时,可以进一步降低多参考帧运动估计的运算量,能够节省约35％的编码时间。     

一种新型H.264/AVC多参考帧预测方法

在H.264/AVC视频压缩标准采用的几项关键技术中,使用多参考帧预测可以增加最佳匹配块的检索概率,进而大大提高了编码效率。受B帧直接(direct)预测模式的启发,提出了一种新的基于扩展帧的多参考帧预测方法,由多参考帧中的共同位置块及其参考块扩展得到一个新的抽取帧,增加了原始序列的时域分辨率,使得扩展帧更加接近当前帧,提高了运动估计中最佳匹配的检索概率,进而提升了编码效率。仿真结果证实该方法的编码性能好于H.264/AVC参考软件。     

面向AVS2的快速帧间预测算法北大核心

新一代具有自主知识产权的视频编码标准AVS2正在制定当中,其相对于上一代标准而言具有更高的编码效率,但由于使用了多划分模式、多参考帧等技术,其编码复杂度也大幅增加。为了提高AVS2帧间编码速度,提出了一种快速帧间预测算法,在使用非对称运动划分(Asymmetric Motion Partitions,AMP)快速决策算法的基础上,深度挖掘同一编码单元下相邻预测单元之间的相关性,利用邻近预测单元来预测当前块的参考帧,通过判断预测单元的运动矢量残差的曼哈顿距离,以确定最佳参考帧,从而减小参与计算的参考帧数目。实验结果表明,该算法在图像质量和比特率基本保持不变的情况下,有效地提高了AVS2的编码速度。     

面向AVS2的快速帧间预测算法

新一代具有自主知识产权的视频编码标准AVS2正在制定当中,其相对于上一代标准而言具有更高的编码效率,但由于使用了多划分模式、多参考帧等技术,其编码复杂度也大幅增加。为了提高AVS2帧间编码速度,提出了一种快速帧间预测算法,在使用非对称运动划分(Asymmetric Motion Partitions,AMP)快速决策算法的基础上,深度挖掘同一编码单元下相邻预测单元之间的相关性,利用邻近预测单元来预测当前块的参考帧,通过判断预测单元的运动矢量残差的曼哈顿距离,以确定最佳参考帧,从而减小参与计算的参考帧数目。实验结果表明,该算法在图像质量和比特率基本保持不变的情况下,有效地提高了AVS2的编码速度。     

Coding statistics based fast mode decision for multi-view video coding

Reduction of high computational complexity of multi-view video coding (MVC) is necessary for realization in consumer electronics. Since mode decision is one of the key computational bottlenecks of multi-view video encoders, this paper proposes a coding statistics based fast mode decision algorithm. First of all, a rate–distortion cost based fast DIRECT mode decision algorithm early terminates the mode decision process if possible. Next, the candidates for Inter modes are reduced by taking the advantage of the correlation between an optimal mode and motion cost. The proper thresholds to reduce the candidates for the above two fast algorithms can be easily derived from exponential functions at run time. Finally, motion vector difference based motion characteristics is referred to further speed up the mode decision process of Inter modes. The experimental results show that the proposed scheme reduces up to 70.82% of encoding time with negligible degradation of RD performance.     

Efficient multi-view video coding using inter-view information

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.     

SIFT-flow-based color correction for multi-view video

During the multi-view video acquisition, color variation across the views tends to be incurred due to different camera positions, orientations, and local lighting conditions. Such color variation will inevitably deteriorate the performance of the follow-up multi-view video processing, such as multi-view video coding (MVC). To address this problem, an effective color correction algorithm, called the SIFT flow-based color correction (SFCC), is proposed in this paper. First, the SIFT-flow technique is used to establish point-to-point correspondences across all the views of the multi-view video. The average color is then computed based on those identified common corresponding points and used as the reference color. By minimizing the energy of the difference yielded between the color of those identified common corresponding points in each view with respect to the reference color, the color correction matrix for each view can be obtained and used to correct its color. Experimental results have shown that the proposed SFCC algorithm is able to effectively eliminate the color variation inherited in multi-view video. By further exploiting the developed SFCC algorithm as a pre-processing for the MVC, extensive simulation results have shown that the coding efficiency of the color-corrected multi-view video can be greatly improved (on average, 0.85 dB, 1.27 dB and 1.63 dB gain for Y, U, and V components, respectively), compared with that of the original multi-view video without color correction.     

Fast motion and disparity estimation for HEVC based 3D video coding

The emerging international standard for high efficiency video coding (HEVC) based 3D video coding (3D-HEVC) is an extension of HEVC. In the test model of 3D-HEVC, variable size motion estimation (ME) and disparity estimation (DE) are both employed to select the best coding mode for each treeblock in the encoding process. This technique achieves the highest possible coding efficiency, but it brings extremely high computational complexity which limits 3D-HEVC from practical applications. In this paper, a fast ME/DE algorithm based on inter-view and spatial correlations is proposed to reduce 3D-HEVC computational complexity. Since the multi-view videos represent the same scene with similar characteristic, there is a high correlation among the coding information from inter-view prediction. Besides, the homogeneous regions in texture video have a strong spatial correlation, and thus spatially neighboring treeblocks have similar coding information. Therefore, we can determine ME search range and skip some specific ME and DE rarely used in the previously coded view frames and spatially neighboring coding unit. Experimental results demonstrate that the proposed algorithm can significantly reduce computational complexity of 3D-HEVC encoding while maintaining almost the same rate-distortion performance.     

Adaptive Multiview Video Coding Scheme Based on Spatiotemporal Correlation Analyses

In this paper, we propose an adaptive multiview video coding scheme based on spatiotemporal correlation analyses using hierarchical B picture (AMVC‐HBP) for the integrative encoding performances, including high compression efficiency, low complexity, fast random access, and view scalability, by integrating multiple prediction structures. We also propose an in‐coding mode‐switching algorithm that enables AMVC‐HBP to adaptively select a better prediction structure in the encoding process without any additional complexity. Experimental results show that AMVC‐HBP outperforms the previous multiview video coding scheme based on H.264/MPEG‐4 AVC using the hierarchical B picture (MVC‐HBP) on low complexity for 21.5%, on fast random access for about 20%, and on view scalability for 11% to 15% on average. In addition, distinct coding gain can be achieved by AMVC‐HBP for dense and fast‐moving sequences compared with MVC‐HBP.     

Iterative search strategy with selective bi-directional prediction for low complexity multiview video coding

The multiview video coding (MVC) extension of H.264/AVC is the emerging standard for compression of impressive 3D and free-viewpoint video. The coding structure in MVC adopts motion and disparity estimation to exploit temporal and inter-view dependencies in MVC. It results in a considerable increase in encoding complexity. Most of the computational burden comes from uni-directional and bi-directional prediction. In this paper, an iterative search strategy is designed to speed up the uni-directional prediction in MVC. It can work with an adaptive search range adjustment through a confidence measure of a loop constraint to obtain both motion and disparity vectors jointly. Furthermore, a selective bi-directional prediction algorithm is proposed to enhance the coding performance by analyzing the statistical characteristics of bi-directional prediction in MVC. Experimental results demonstrate that, by using the proposed fast search, the temporal and inter-view redundancies of multiview video can be eliminated sufficiently with low complexity.     

采用灰度共生矩阵进行深度预判的3D-HEVC深度图帧内快速编码算法

针对3D视频的3D-HEVC编码标准以多视点纹理视频和深度视频格式进行编码,其深度图编码仍延续纹理视频编码的模式和编码尺寸遍历选择,使得3D-HEVC的编码复杂度居高不下。本文针对深度图帧内预测编码,采用灰度共生矩阵对深度图中的CTU进行计算,统计并分析其矩阵中非零值个数与CTU分割深度的关系,根据非零值个数分布规律,设定阈值,使得帧内编码时可以预判编码模块的分割深度,从而选择性跳过部分不同深度CU的帧内预测过程。经过HTM16.0测试平台的检验,本算法在全帧内编码模式下,测试序列合成视点比特率仅增加0.08%的同时,平均节省了16.8%的编码时间,与其他同类较新算法在HTM16.0平台上的性能比较也有一定的优势。      

Fast macroblock encoding algorithm based on rate-distortion activity for multiview video coding

Multiview video coding (MVC) is the appendix H of H.264/AVC, and it requires a great amount of time to compress multiple viewpoints׳ video with complex prediction structures. To reduce the whole computational complexity of MVC, this paper proposes a fast macroblock (MB) encoding algorithm based on rate-distortion (RD) activity, and it includes the fast mode decision and the fast motion/disparity estimation. First, the RD activity type of the current MB is calculated by utilizing the Skip/Direct RD cost and the average RD costs of classified MB modes. Then, through utilizing the RD activity type and RD costs of the estimated modes, the selection of candidate modes, the early decision of Skip/Direct mode, and the reduction of Inter8×8 mode estimation are all presented in the fast mode decision. By using the RD activity type and the correlations of vectors, the selection of search center and the prediction of search range are introduced in the fast motion/disparity estimation. In addition, the proposed algorithm can be applied to temporal and inter-view views as well as anchor and non-anchor frames. An experiment with a wide range of video scenes, camera setups and quantization parameters was implemented, and the results confirmed that the proposed algorithm can reduce the encoding time significantly while maintaining a similar RD performance as the original MVC encoder. Compared to the state-of-the-art algorithms, the proposed algorithm also demonstrated better performances in the various test cases.     

Fast sample adaptive offset algorithm for 360-degree video coding

360-degree video is becoming popular with the development of the virtual reality(VR) technology in recent years. For this kind of video, pictures are projected to a two-dimensional plane. Standard video encoders are used for compression. Due to the projection mapping of the spherical video to the two-dimensional plane video, many conventional coding tools can be adjusted properly for better performance. As the 360-degree videos are high resolution videos, usually 8K resolution videos, the high complexity for encoding 360-degree videos is a problem to be solved urgently, especially for the latest video standard H.265/HEVC. Sample adaptive offset (SAO) is a new tool adopted in H.265/HEVC. It can reduce ringing artifacts and achieve higher coding efficiency. But it also introduces high computational complexity, especially on high resolution videos. In this paper, a fuzzy control based fast SAO method is proposed to reduce the high computational complexity in SAO encoding process according to the characteristics of the ERP format video. Compared with the original algorithm in the reference software HM 16.14, experimental results show that the proposed method can reduce about 73% SAO encoding time on average under the common test conditions with negligible loss.