低复杂度的多视点视频编码宏块模式决策算法

为了降低多视点视频编码(MVC)的计算复杂度,提出了一种基于全局-局部率失真代价的低复杂度宏块模式决策算法。首先根据宏块候选模式的块尺寸和率失真代价特点,将所有候选模式分为大尺寸模式(Skip/Direct、Inter16×16和Intra16×16)和小尺寸模式(Inter16×8、Inter8×16、Inter8×8、Intra8×8和Intra4×4);接着统计已编码帧中这两类宏块模式的平均率失真代价,并利用这些平均率失真代价计算当前帧宏块模式决策的全局率失真代价;最后利用得到的全局率失真代价,并结合当前宏块已估计模式的局部率失真代价和空间邻近宏块的模式信息提前终止模式决策,具体包括对大尺寸宏块模式进行提前判定以及对小尺寸候选模式进行逐级选择。实验结果表明:与MVC参考代码中的全搜索模式决策算法相比,本文算法在时域预测视点和视点域预测视点上分别节省了74%和82%的平均编码时间,同时保持了良好的编码率失真性能;与现有模式决策快速算法相比,本文算法降低了更多的编码时间,并具有更好的编码率失真性能。     

基于局部残差复杂度的快速帧间模式选择

针对H.264传统帧间模式选择算法的高复杂度,提出了一种适合各种视频分辨率格式的快速帧间模式选择算法。该算法基于局部残差复杂度(local residual complexity,LRC),通过给局部残差复杂度设定阈值来决定宏块的活跃度,再根据宏块的活跃度选出候选的帧间模式,由此进行率失真优化(Rate-distortion Optimization,RDO)计算,从而减少了不必要帧间模式的RDO计算,取得了较高的编码效率。实验结果表明,与JM18.4默认的帧间模式选择算法相比,该算法在峰值信噪比和码率基本不变的前提下,可以平均减少大约60%的运动估计时间。     

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。     

基于转移概率的多视点视频快速模式选择算法

针对多视点视频编码(MVC)中部分大宏块模式(SKI P/DIRECT模式,帧间16×16模式)相对于其它模式的计算复杂 度低,并且在编码所确定的最优模式中占有相当高比重的特点,本文提出一种基于转移概率 的多视点视频 快速模式选择算法。首先根据多视点视频当前编码宏块对应时间和视点间宏块及周围宏块的 位置几何关系, 建立宏块模式参考模型;其次比较参考模型中模式的时间相似度和视点间相似度;最后计算 模式之间的转 移概率,确定提前结束大宏块模式选择过程的阈值。实验结果表明,本文所提出的快速算法 平均节约MVC时间80.93%,编码质量平均下降0.04dB,码率平均增加0.27%。     

H.264的帧间宏块模式选择算法

H.264中定义了7种不同大小的帧间宏块模式,为了提高编码效率,编码时对每一种宏块模式都进行运动搜索,并利用率失真优化(RDO)分别计算编码代价,选择编码代价最小的模式作为帧间编码模式,但是计算量非常大,导致运动估计速度缓慢,很难实现实时编码。本文提出一种选择宏块模式的快速算法,通过宏块模式编码代价的比较,提前确定宏块模式,从而逐步减少不必要的宏块搜索和RDO计算。实验结果表明,此方法与全宏块模式搜索相比较,图像质量和码流只有少量变化,而编码速度有显著提高。     

H.264的帧间宏块模式选择算法

H.264中定义了7种不同大小的帧间宏块模式，为了提高编码效率，编码时对每一种宏块模式都进行运动搜索，并利用率失真优化（RDO）分别计算编码代价，选择编码代价最小的模式作为帧间编码模式，但是计算量非常大，导致运动估计速度缓慢，很难实现实时编码。本文提出一种选择宏块模式的快速算法，通过宏块模式编码代价的比较，提前确定宏块模式，从而逐步减少不必要的宏块搜索和RDO计算。实验结果表明，此方法与全宏块模式搜索相比较，图像质量和码流只有少量变化，而编码速度显著提高。     

结合像素域JND阈值空间相关性与图像块类型的残差滤波算法

为了更好地将人眼视觉感知特性应用于视频压缩系统,从而去除视频的视觉冗余成分,在利用像素域的恰可察失真(Just Noticeable Distortion,JND)阈值的基础上,结合JND阈值的空间相关性与图像块类型,提出了一种改进的残差滤波算法。该算法首先在像素域计算出每个像素的JND阈值,然后在变换单元(Transform Unit,TU)中挖掘每个像素JND阈值与其周围邻近像素JND阈值之间的空间相关性,再利用索贝儿(Sobel)边缘检测算子将TU分成不同类型的图像块,并且计算出对应的复杂度因子,最后结合上述像素JND阈值的空间相关性和TU复杂度因子对TU残差进行滤波。提出的算法模型可以嵌入到高效率视频编码(High Efficiency Video Coding,HEVC)框架。实验结果表明,在全I帧配置下,提出的算法与标准算法HM16.0相比,在人眼主观感知质量基本一致的情况下,平均可节省16.1%的码率。     

基于动态多阈值的多视点视频编码宏块模式快速选择算法

本文分析了多视点视频编码中宏块模式选择情况的统计特性,把宏块模式分为四类.提出了基于宏块模式类率失真均值的多阈值快速宏块模式选择算法及阈值的近似计算方法和动态更新算法,理论分析了该快速算法的编码率失真性能.实验结果表明,所提出快速算法在几乎不影响编码率失真性能的情况下,编码速度比多视点视频编码校验模型提高1.92倍到7.07倍.     

基于梯度方向算子的H.264帧内模式选择算法

提出梯度方向算子的概念,基于该算子提出了一种H.264帧内模式快速选择算法。本文首先应用梯度方向算子计算编码宏块中各4×4亮度子块的纹理特征和灰度起伏特征,根据这两种特征参量削减4×4帧内候选预测模式。通过统计宏块中各子块的4×4候选预测模式信息,结合梯度方向强度门限判别法削减宏块的16×16候选预测模式,通过率失真优化算法计算得到最优亮度预测模式。进一步根据亮度宏块和色度宏块的对应关系,在亮度候选预测模式的基础上对色度宏块候选预测模式进行削减,最后计算得到最优色度预测模式。该算法削减了50%以上的帧内预测模式,减少了帧内预测模式选择的运算量,实验表明,该算法能够在峰值信噪比和码流比特率变化轻微的前提下减少50%以上的运算量。      

结合深度信息的多视点视频编码快速模式选择算法

多视点视频加深度(MVD,multi-view video plus depth)的编码格式包含多个纹理视频序列及其对应的深度图,深度图与对应的纹理视频具有相似的边缘信息。传统的编码模式不考虑两者的联系,单独编码导致复杂度高、编码时间过长。因此,合理利用深度图与纹理图的相似性进行编码,可以有效降低编码复杂度,同时应该确保编码质量不受影响。本文利用深度图的这一特点辅助纹理视频的编码,提出一种帧间快速模式选择算法,充分利用深度图与纹理图之间的相似性,建立一种联合复杂度模型,根据模型得到每个宏块的复杂度。对于复杂度低的宏块,在计算率失真代价之前跳过编码中一些不必要的模式,从而降低编码复杂度。实验表明,本文提出的快速模式选择算法,在保证率失真性能基本不变的情况下,能减少60.57%的编码复杂度,并最高能减少80.64%的编码时间。     

Selective Disparity Estimation and Variable Size Motion Estimation Based on Motion Homogeneity for Multi-View Coding

Multi-view video coding (MVC) is an ongoing standard in which variable size disparity estimation (DE) and motion estimation (ME) are both employed to select the best coding mode for each macroblock (MB). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs it from practical use. In this paper, a fast DE and ME algorithm based on motion homogeneity is proposed to reduce MVC computational complexity. The basic idea of the method is to utilize the spatial property of motion field in prediction where DE and variable size ME are needed, and only in these regions DE and variable size ME are enabled. The motion field is generated by the corresponding motion vectors (MVs) in spatial window. Simulation results show that the proposed algorithm can save 63% average computational complexity, with negligible loss of coding efficiency.      

Adaptive Block-size Transform based Just-Noticeable Difference model for images/videos

In this paper, we propose a novel Adaptive Block-size Transform (ABT) based Just-Noticeable Difference (JND) model for images/videos. Extension from 8×8 Discrete Cosine Transform (DCT) based JND model to 16×16 DCT based JND is firstly performed by considering both the spatial and temporal Human Visual System (HVS) properties. For still images or INTRA video frames, a new spatial selection strategy based on the Spatial Content Similarity (SCS) between a macroblock and its sub-blocks is proposed to determine the transform size to be employed to generate the JND map. For the INTER video frames, a temporal selection strategy based on the Motion Characteristic Similarity (MCS) between a macroblock and its sub-blocks is presented to decide the transform size for the JND. Compared with other JND models, our proposed scheme can tolerate more distortions while preserving better perceptual quality. In order to demonstrate the efficiency of the ABT-based JND in modeling the HVS properties, a simple visual quality metric is designed by considering the ABT-based JND masking properties. Evaluating on the image and video subjective databases, the proposed metric delivers a performance comparable to the state-of-the-art metrics. It confirms that the ABT-based JND consists well with the HVS. The proposed quality metric also is applied on ABT-based H.264/Advanced Video Coding (AVC) for the perceptual video coding. The experimental results demonstrate that the proposed method can deliver video sequences with higher visual quality at the same bit-rates.     

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.     

Early SKIP mode decision for MVC using inter-view correlation

In the joint multiview video model (JMVM) proposed by JVT, the variable block-size motion estimation (ME) and disparity estimation (DE) have been employed to determine the best coding mode for each macroblock (MB). These give a high coding efficiency for multiview video coding (MVC), however, they cause a very high computational complexity in encoding system. This paper proposes to reduce the complexities of the ME and DE processes with an early SKIP mode decision algorithm based on the analysis of prediction mode distribution regarding the corresponding MBs in the neighbor view. In this method, the mode decision procedures of most of MBs can be early terminated, and thus much of computation for ME and DE can be greatly reduced. Simulation results demonstrate that our algorithm can achieve computational saving of 46–57% (depending on the tested sequences) with no significant loss of rate-distortion performance.     

多视点编码中一种快速的模式选择方法

在多视点视频编码中,多尺寸的运动估计和视点估计被用来选择宏块的最优编码模式。这些技术大大提高了编码效率,但是却带来了庞大的计算复杂度,从而影响了多视点视频编码的广泛应用。提出了一种新的模式选择的快速算法,利用了相邻视点的模式相关性来减少执行不需要的模式。实验表明,所提出的快速模式选择算法在不降低编码效率的同时可以显著降低计算复杂度。     

Content-adaptive motion estimation algorithm for coarse-grain SVC

A joint model of scalable video coding (SVC) uses exhaustive mode and motion searches to select the best prediction mode and motion vector for each macroblock (MB) with high coding efficiency at the cost of computational complexity. If major characteristics of a coding MB such as the complexity of the prediction mode and the motion property can be identified and used in adjusting motion estimation (ME), one can design an algorithm that can adapt coding parameters to the video content. This way, unnecessary mode and motion searches can be avoided. In this paper, we propose a content-adaptive ME for SVC, including analyses of mode complexity and motion property to assist mode and motion searches. An experimental analysis is performed to study interlayer and spatial correlations in the coding information. Based on the correlations, the motion and mode characteristics of the current MB are identified and utilized to adjust each step of ME at the enhancement layer including mode decision, search-range selection, and prediction direction selection. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of SVC while maintaining nearly the same rate distortion performance as the original encoder.     

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.     

Efficient early direct mode decision for multi-view video coding

Multi-view video coding (MVC) uses various prediction modes and exhaustive mode decision to achieve high coding efficiency. However, the introduced heavy computational complexity becomes the bottleneck of the practical application of MVC. For this, an efficient early Direct mode decision for MVC is proposed in this paper. Based on the observation that the Direct mode is highly possible to be the optimal mode, the proposed method first computes the rate distortion (RD) cost of the Direct mode and compares this RD cost value with an adaptive threshold for providing an early termination chance as follows. If this RD cost value is smaller than the adaptive threshold, the Direct mode will be selected as the optimal mode and the checking process of the remaining modes will be skipped; otherwise, all the modes will be checked to select the one with the minimum RD cost as the optimal mode. Note that the above-mentioned adaptive threshold is determined as the median prediction value of a set of thresholds, which are derived by using the spatial, temporal and inter-view correlations between the current macroblock (MB) and its neighboring MBs, respectively. Experimental results have demonstrated that the proposed method is able to significantly reduce the computational complexity of MVC with negligible loss of coding efficiency, compared with the exhaustive mode decision in MVC.     

基于纹理分解的变换域JND模型及图像编码方法

为了提高变换域JND模型的精度,在计算对比度掩盖因子时只对纹理分量滤波并判断区域类型的方法避免了JND低估的问题。将改进的JND模型用于图像编码,考虑到辅助信息对编码效率的影响,把经过调整后的JND模型结合到量化过程中,能去除更多的视觉冗余并保持兼容性。仿真结果表明,纹理分解的方法提高了JND阈值,改进的编码方法在相似的视觉质量下能节省更多的码率并且不需要增加额外的比特开销,该编码思路也适用于视频编码。