Implementation of Multiple Macroblock Mode Overlapped Block Motion Compensation for Wavelet Video Coding

This paper proposes a hybrid video coding framework based on discrete wavelet transform and multiple macroblock mode overlapped block motion compensation (OBMC). Studying the neighborhood in multiple macroblock mode situations, we set rules for the selection of neighboring blocks in OBMC. Based on experimental results, the raised cosine window and the best neighboring blocks are chosen for their outstanding performance. The multiple macroblock mode OBMC has a good performance in reducing the blocking effect, and the coding efficiency is improved. The proposed scheme can provide a 1 dB coding gain compared to MPEG-4, and its performance is close to the latest H.264 standard. From a subjective point of view, the new framework is also better than the standards.     

Analysis of space-dependent characteristics of motion-compensatedframe differences based on a statistical motion distribution model

Although it has been observed that motion-compensated frame differences increase toward block boundaries and overlapped block motion compensation (OBMC) has been shown to provide reduced blocking artifacts as well as improved prediction accuracy, there is almost no satisfactory theoretical basis that clearly interprets the space-dependent characteristics of motion-compensated frame differences, nor have the theoretical aspects of OBMC been investigated thoroughly. We first interpret the space-dependent characteristics of motion-compensated frame differences based on a novel statistical motion distribution model. We then apply the statistical motion distribution model to the analysis of prediction efficiency of OBMC. Through the analysis, we prove theoretically that OBMC can reduce and equalize the motion-compensated frame differences across a block. The analytical results are justified by empirical experiments with typical image sequences.     

Overlapped block motion compensation: an estimation-theoreticapproach

We present an estimation-theoretic analysis of motion compensation that, when used with fields of block-based motion vectors, leads to the development of overlapped block algorithms with improved compensation accuracy. Overlapped block motion compensation (OBMC) is formulated as a probabilistic linear estimator of pixel intensities given the limited block motion information available to the decoder. Although overlapped techniques have been observed to reduce blocking artifacts in video coding, this analysis establishes for the first time how (and why) OBMC can offer substantial reductions in prediction error as well, even with no change in the encoder's search and no extra side information. Performance can be further enhanced with the use of state variable conditioning in the compensation process. We describe the design of optimized windows for OBMC. We also demonstrate how, with additional encoder complexity, a motion estimation algorithm optimized for OBMC offers further significant gains in compensation accuracy. Overall mean-square prediction improvements in the range of 16 to 40% (0.8 to 2.2 dB) are demonstrated     

A parametric solution for optimal overlapped block motioncompensation

We find the optimal window for overlapped block motion compensation (OBMC) by statistically modeling the motion field, the field of block motion estimates and their relationship. This enables us to show how the optimal OBMC window is affected by random field parameters, such as the variance of the motion field and the correlation coefficients of both the intensity field and the motion field. The OBMC window obtained in this fashion is shown to have good performance in reducing the prediction error. Furthermore, this parametric solution provides insight into motion uncertainty and the overlapped motion compensation process.     

Motion estimation methods for overlapped block motion compensation

An extension of conventional block motion compensation (BMC), overlapped block motion compensation (OBMC) has been shown to reduce residual errors and blocking effects in motion-compensated video. However, the overlap creates a noncausal spatial dependence between blocks and complicates motion estimation (ME) for OBMC. Iterative methods have traditionally been employed for overlapped block motion estimation (OBME). For compression, the rate for the motion vector field (MVF) may also be constrained. This work considers several rate-constrained OBME algorithms, both iterative and noniterative. Experiments demonstrate that a simple raster-scan algorithm is effective as a suboptimal, noniterative solution, with comparable or better rate-distortion performance and computational complexity than iterative OBME algorithms. Depending on the application, either this method or a simple block-matching algorithm plus iteration are the most attractive of the tested OBME schemes.     

自适应联合相邻运动矢量的运动补偿插值算法

帧率上采样作为一种视频后处理技术,通过对原始视频插值得到高帧率视频,满足人们对高帧率视频的需求.传统基于重叠块的插值补偿算法会带来块效应或鬼影现象.为了解决这一问题,人们提出联合匹配块及其相邻块预测的方法,但是复杂度高,效果不明显.基于以上几点,本文提出一种自适应联合相邻运动矢量的运动补偿插值算法(Joint Motion-Compensated In-terpolation Algorithm Using Adjacent Block Motion Vectors Adaptively,AJ-MCI).在该算法中,将运动矢量矫正和运动补偿插值算法相结合,同时运动补偿模块中自适应地联合相邻匹配块,以最大限度刻画真实运动轨迹.实验结果表明,本文算法能很好的提升视频的主客观质量,同时保持较低计算复杂度.     

低码率视频压缩技术的块效应消除方法

低友率视频压缩技术是多媒体通信的关键技术。基于块编码的低码率视频压缩技术中,块效应现象成为比较突出的问题。本文讨论了低码率视频压缩中消除块效应的方法,提出了基于约束复原原理的一种具体块效应消除方法,并根据计算机软件实现的分析,得出了结论采用约束复原的块应消除方法可以同时提高客观ＰＳＮＲ值和改善块应现象。     

VLSI Architecture of Block Matching Algorithms for Motion Estimation in High Efficiency Video Coding

High-efficiency video coding (HEVC) is a latest video coding standard and the motion estimation unit is the most important block. The work presents the different types of Matching Criteria for Block-Based Motion Estimation technique in HEVC standard. HEVC requires fast motion estimation algorithms to have better real time performance. The hardware implementation of motion estimation helps to achieve high speed though parallel processing. An improved block matching technique is designed with reduced blocks for HEVC. The proposed method has less execution time where only blocks having motion are compared for prediction computation. The searching time complexity is dependent on the number of blocks that are having motion. The searching time of frame having small motion can be reduced to 80–85% as compared to the traditional full search algorithm. In the paper, sum of absolute difference, mean square error and mean absolute difference are computed to find the best matching algorithm for HEVC. However, SAD has less computational complexity with compare to other matching criteria. The results suggest that proposed motion estimation algorithm has better performance with compare to similar previous work.

     

Error Concealment Using Intra‐Mode Information Included in H.264/AVC‐Coded Bitstream

The H.264/AVC standard has adopted new coding tools such as intra‐prediction, variable block size, motion estimation with quarter‐pixel‐accuracy, loop filter, and so on. The adoption of these tools enables an H.264/AVC‐coded bitstream to have more information than was possible with previous standards. In this paper, we propose an effective spatial error concealment method with low complexity in H.264/AVC intra‐frame. From information included in an H.264/AVC‐coded bitstream, we use prediction modes of intra‐blocks to recover a damaged block. This is because the prediction direction in each prediction mode is highly correlated to the edge direction. We first estimate the edge direction of a damaged block using the prediction modes of the intra‐blocks adjacent to a damaged block and classify the area inside the damaged block into edge and flat areas. Our method then recovers pixel values in the edge area using edge‐directed interpolation, and recovers pixel values in the flat area using weighted interpolation. Simulation results show that the proposed method yields better video quality than conventional approaches.     

Adaptive Pixel Interpolation for Spatial Error Concealment

Error concealment techniques are widely used as efficient ways to recover the lost information at the decoder. This paper proposes an adaptive pixel interpolation technique for spatial error concealment in the block based coding system. For a missing pixel in a corrupted block, its value is derived from four neighborhoods of the block through interpolation using multiple prediction strategy. The weighting rules of these four neighborhood blocks are carefully designed with regard to three factors, the distance to the missing pixels within the given corrupted block, the percentage of uncorrupted pixels, and the similarity to the given corrupted block. The proposed method works effectively in consecutive block loss situation, which is common in real applications of video transmission. Experimental results show the proposed technique gains more accurate recovery of the missing pixels than the existing schemes.     

Image filtering in the block DCT domain using symmetric convolution

Processing of images in the transform domain saves computation by avoiding inverse and re-transform operations. In this paper, we present a technique for filtering of images in the transform domain using symmetric convolution in the block DCT space. Due to the application of convolution-multiplication property in the DCT domain, the filtering operation requires significantly less computation than its equivalent in the original signal/image space. To take care of discontinuities along boundaries of blocks, filtering is performed on a larger DCT block composed from adjacent blocks. Subsequently, the filtered DCT block is obtained by decomposing it. The proposed filtering technique achieves the same results of linear convolution in the spatial domain with reduced cost. With the proposed filtering, it is possible to significantly speedup the operation by ignoring some elements in the filtering matrices whose magnitudes are smaller than a threshold value. Typical sparseness of DCT domain input blocks is also considered for further reduction of computational cost. The proposed method uses simple linear operations such as matrix multiplication, which is appropriate for efficient hardware implementations. We also demonstrate its applications in image sharpening and removal of blocking artifacts directly in the compressed domain.     

基于稠密矢量场及自适应补偿的帧率上变换

为了有效解决视频帧率上变换中物体边缘出现的模糊和块效应等问题,结合运动估计,优化了矢量化后处理和运动补偿算法.在基于块的运动估计中,结合运动的时空相关性优化块匹配算法,提高物体边缘运动矢量的准确性;通过基于像素块相关性的插值算法,获取像素矢量场,并保持物体结构完整性;在运动补偿时,结合矢量后处理的分类信息,自适应地进行加权插值计算,提高内插帧的质量.实验结果表明,与传统方法相比,该方法在主观和客观质量上都有较大的提升.     

Reference frame modification techniques for temporal and spatial scalability

Compressed video is usually transmitted over channels which are not necessarily error free. Channel errors can result in a mismatch between the encoder and the decoder, and because of the predictive structures used in video coding, the errors will propagate both temporally and spatially. Consequently, the quality of the received video at the decoder may degrade significantly. In order to improve the quality of the received video, several error resilient methods have been proposed. In this paper, the introduced mismatch is reduced by modifying the prediction structure and forming a more robust reference frame. The proposed technique combines error robustness of previous Intra coded blocks, better prediction achieved using the previous reference frame, and exponential decay of error propagation caused by the leaky prediction. This technique was examined with the scalable extension of H.264/AVC. Furthermore, the technique was also used in combination with random Intra refresh and error resilience mode decision techniques to achieve better robustness. Simulation results show the effectiveness of our scheme, especially for medium and high motion sequences.     

Test Data Compression Using Selective Sparse Storage

For today’s very large scale integrated circuits, test data volume is recognized as a major contributor to the cost of manufacturing testing. Test data compression addresses this problem by reducing the test data volume without affecting the overall system performance. This paper proposes a new test data compression technique using selective sparse storage. Test sets are partitioned into four kinds of blocks of uniform length, all-0 blocks, all-1 blocks, sparse blocks and characterless blocks. Blocks are encoded appropriately based on the occurrence of them. They are encoded into 0, 10, 110 + number of the sparse bits + locations of all the sparse bits, and 111 + the block itself, respectively. Two algorithms are proposed for how to select the sparse blocks from test sets. A theoretical analysis for our selective sparse storage shows the new compression technique outperforms the conventional test data compression approaches. Experimental results illustrate the flexibility and efficiency of the new method, which is consistent with the theoretical analysis.     

Fuzzy Logic Based Temporal Error Concealment for H.264 Video

In this paper, a new error concealment algorithm is proposed for the H.264 standard. The algorithm consists of two processes. The first process uses a fuzzy logic method to select the size type of lost blocks. The motion vector of a lost block is calculated from the current frame, if the motion vectors of the neighboring blocks surrounding the lost block are discontinuous. Otherwise, the size type of the lost block can be determined from the preceding frame. The second process is an error concealment algorithm via a proposed adapted multiple‐reference‐frames selection for finding the lost motion vector. The adapted multiple‐reference‐frames selection is based on the motion estimation analysis of H.264 coding so that the number of searched frames can be reduced. Therefore the most accurate mode of the lost block can be determined with much less computation time in the selection of the lost motion vector. Experimental results show that the proposed algorithm achieves from 0.5 to 4.52 dB improvement when compared to the method in VM 9.0.     

一种改进的基于后处理去除块效应算法

在基于DCT压缩编码系统中,DCT都是基于模块的。即首先将图像分成8×8的像素块,然后对每块进行DCT得到64个DCT系数。但由于是分别对每块进行DCT,块与块之间的相关性被忽略,导致所谓的“块效应”。文中提出了一种改进的基于后处理的去块效应方法。在图像重建时,首先在块与块之间提出了4种模式,包括了3个与频率相关的模式和4个块拐角处的拐角模式。然后对不同模式下采用低复杂度的去块效应滤波器,最后重建图像。不论是视觉效果还是图像质量都有所提升。     

分布式视频编码边信息改进技术

高质量的边信息生成技术是分布式视频编码系统实现高压缩效率的关键所在.提出一种边信息的改进方法,对部分译码的Wyner-Ziv(WZ)帧中运动剧烈的区域进行空域修正,使用相邻关键帧对应块的空间预测值与实际值之间的差值来补偿当前部分译码WZ帧中空间预测的误差.仿真结果表明该方法提升了边信息的质量,进而提高了DVC系统的率失真性能.     

基于边界先验双模型贝叶斯决策的红外图像海天线检测

为了解决复杂海面干扰下海天线检测的问题,本文提出了一种基于边界先验双模型贝叶斯决策的红外图像的海天线检测方法。该方法首先将海空背景下的红外图像划分为子图像块,以子图像块的离散余弦变换的主余弦谱作为子图像块特征;然后,基于边界先验建立了海、天子图像块的贝叶斯决策模型,对海、天子图像块进行粗划分;之后,利用粗划分的子图像块集合建立细划分贝叶斯决策模型,利用重叠子图像块滑动细划分方法,获取海天线上候选点;最后,利用随机抽样一致性（RANSAC）算法得到海天线模型参数,实现海天线的检测。实验结果表明,该方法能有效检测出复杂海空背景下的海天线,对于海杂波、亮斑等干扰较多的复杂红外图像具有更优的检测效果,运算速度较快。      

一种有效的MIMO OFDM信道估计方法

传统的MIMO OFDM信道估计方法总是假设信道在由若干OFDM符号组成的每一帧的传输过程中保持不变,但这个假设在快变信道的条件下就不成立了.本文提出了一种适合快变信道的有效的估计方法.该方法通过在每个OFDM符号中设置若干训练子载波来跟踪快变的信道.首先讨论了在每个OFDM符号中所需的训练子载波的数目及其相应的位置,给出了在多发射天线多接收天线条件下的训练子载波的正交结构,然后在估计出训练子载波处的信道频率响应后.提出了一种不同于根据邻近训练子载波进行线性插值的以获得用于传输数据的子载波的信道频率响应的方法.仿真结果表明了我们所提出的方法的有效性.