Modified CLT-domain motion estimation based on phase correlation

In this paper, a Modified Complex Lapped Transform domain Motion Estimation (MCLT-ME) method to estimate the motion of video sequence is proposed. The proposed method is based on phase correlation of current window region and corresponding window region, and provides a significant improvement in motion estimation.     

H.264 motion estimation algorithm based on video sequences activity

Motion estimation is an important part of H.264/AVC encoding progress, with high computational complexity. Therefore, it is quite necessary to find a fast motion estimation algorithm for real-time applications. The algorithm proposed in this letter adjudges the macroblocks activity degree first; then classifies different video sequences, and applies different search strategies according to the result. Experiments show that this method obtains almost the same video quality with the Full Search （FS） algorithm but with reduced more than 95% computation cost.     

A FINE GRANULAR JOINT SOURCE CHANNEL CODING METHOD

An improved FGS (Fine Granular Scalability) coding method is proposed in this letter,which is based on human visual characteristics.This method adjusts FGS coding frame rate according to the evaluation of video sequences so as to improve the coding efficiency and subject perceived quality of reconstructed images.Finally,a fine granular joint source channel coding is proposed based on the source coding method,which not only utilizes the network resources efficiently,but guarantees the reliable transmission of video information.     

Motion-based region growing segmentation of image sequences

This paper proposes a motion-based region growing segmentation scheme for the object-based video coding, which segments an image into homogeneous regions characterized by a coherent motion. It adopts a block matching algorithm to estimate motion vectors and uses morphological tools such as open-close by reconstruction and the region-growing version of the watershed algorithm for spatial segmentation to improve the temporal segmentation. In order to determine the reliable motion vectors, this paper also proposes a change detection algorithm and a multi-candidate pro- screening motion estimation method. Preliminary simulation results demonstrate that the proposed scheme is feasible. The main advantage of the scheme is its low computational load.     

MOTION COMPENSATION BASED ON MOTION VECTOR INTERPOLATION

A modified block matching algorithm (BMA) with motion correlation constraint (MCCBMA) is proposed at first. Then a novel motion compensation algorithm (INTPMC) which computes motion vector for each pixel by interpolating motion vectors is presented. In order to increase interframe prediction performance and decrease the computational complexity, an optimizing algorithm for partial motion vectors is described at last. Experimental results show that the proposed algorithm can improve the prediction performance obviously with a moderately increased complexity compared with the conventional full search block matching algorithm (FSBMA).     

POLYNOMIAL MODEL BASED FAST FRACTIONAL PIXEL SEARCH ALGORITHM FOR H.264/AVC

This paper proposed a novel fast fractional pixel search algorithm based on polynomial model. With the analysis of distribution characteristics of motion compensation error surface inside tractional pixel searching window, the matching error is fitted with parabola along horizontal and vertical direction respectively. The proposcd searching strategy needs to check only 6 points rather than 16 or 24 points, which are used in the l lierarchical Fractional Pel Search algorithm （HFPS） for 1/4-pel and 1/8-pel Motion Estimation （ME）. The experimental results show that the proposed algorithm shows very good capability in keeping the rate distortion performance while reduces computation load to a large extent compared with HFPS algorithm.     

Optimized meanshift target reference model based on improved pixel weighting in visual tracking

The generic Meanshift is susceptible to interference of background pixels with the target pixels in the kernel of the reference model, which compromises the tracking performance. In this paper, we enhance the target color feature by attenuating the background color within the kernel through enlarging the pixel weightings which map to the pixels on the target. This way, the background pixel interference is largely suppressed in the color histogram in the course of constructing the target reference model. In addition, the proposed method also reduces the number of Meanshift iterations, which speeds up the algorithmic convergence. The two tests validate the proposed approach with improved tracking robustness on real-world video sequences.     

AN HMM BASED ANALYSIS FRAMEWORK FOR SEMANTIC VIDEO EVENTS

Semantic video analysis plays an important role in the field of machine intelligence and pattern recognition. In this paper, based on the Hidden Markov Model （HMM）, a semantic recognition framework on compressed videos is proposed to analyze the video events according to six low-level features. After the detailed analysis of video events, the pattern of global motion and five features in foreground-the principal parts of videos, are employed as the observations of the Hidden Markov Model to classify events in videos. The applications of the proposed framework in some video event detections demonstrate the promising success of the proposed framework on semantic video analysis.     

All zero macroblock decision method for H.26L

In order to reduce the computation in the part of motion search and transform in H.26L encoder, an all-zero macroblock decision method based on integer transform and motion search is proposed in this paper. According to the characteristics of integer transform and motion search in H.26L, all-zero macroblock decision is made in inter frame coding by comparing Sum of the Absolute Differences(SAD) with a value related with Quantization Parameter(QP) before integer transform. It avoids a large amount of computation in motion search, transform and quantization. This technology highly improves the efficiency of real time H.26L encoder by skipping all-zero macroblock before integer transform and shortening the code stream at the same time.     

Electronic image stabilization algorithm based on fixed-lag smooth filtering

An algorithm using fixed-lag smooth filtering to improve the precision of EIS algorithm is presented in this paper. Firstly, gray projection algorithm (GPA) is used to calculate the interframe global motion vectors. Secondly, the fixed-lag smooth filter is used to smoothen the motion track of the original video sequence, according to different motion models. At last, the original sequence is compensated by using the compensation vectors calculated from filtering. This algorithm has been proved superior in filtering precision by experiments of video sequences in different motion scenes. This algorithm also satisfies the real-time request.     

A variable block size motion estimation algorithm for real-time H.264 video encoding

This paper presents an efficient variable block size motion estimation algorithm for use in real-time H.264 video encoder implementation. In this recursive motion estimation algorithm, results of variable block size modes and motion vectors previously obtained for neighboring macroblocks are used in determining the best mode and motion vectors for encoding the current macroblock. Considering only a limited number of well chosen candidates helps reduce the computational complexity drastically. An additional fine search stage to refine the initially selected motion vector enhances the motion estimator accuracy and SNR performance to a value close to that of full search algorithm. The proposed methods result in over 80% reduction in the encoding time over full search reference implementation and around 55% improvement in the encoding time over the fast motion estimation algorithm (FME) of the reference implementation. The average SNR and compression performance do not show significant difference from the reference implementation. Results based on a number of video sequences are presented to demonstrate the advantage of using the proposed motion estimation technique.     

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.

     

Fast encoding techniques for Multiview Video Coding

Multiview Video Coding (MVC) is a technique that permits efficient compression of multiview video. MVC uses variable block size motion and disparity estimation for block matching. This requires an exhaustive search process that involves all possible macroblock partition sizes. We analyze the time complexity of MVC and the methods that have been proposed to speed up motion and disparity estimation. We then propose two new methods: Previous Disparity Vector Disparity Estimation (PDV-DE) and Stereo-Motion Consistency Constraint Motion and Disparity Estimation (SMCC-MDE). PDV-DE exploits the correlation between temporal levels and disparity vectors to speed up the disparity estimation process while SMCC-MDE exploits the geometrical relationship of consecutive frame pairs to speed up motion and disparity estimation. We build a complete low complexity MVC encoding solution that combines our two methods with complementary previous methods to speed up motion and disparity search. We evaluate the complexity of our solution in terms of encoding time and number of search points. Our experimental results show that our solution can reduce the encoding time and number of search points of the standard MVC implementation (JMVM 6.0) using the fast TZ search mode up to 93.7% and 96.9%, respectively, with negligible degradation in the rate-distortion performance. Compared to the best published results, this is an improvement of up to 11% and 7%, respectively.     

基于GA的压缩域中全局运动估计及在字幕遮挡区域恢复中的应用

文章提出了一种直接使用压缩域中的运动矢量进行全局运动估计的方法,并用遗传算法优化输入运动矢量与全局运动参数所产生运动矢量的平均匹配误差.最终的实验结果表明本文的方法能够很好的估计出全局运动的参数.并且提出了一种运用全局/局部运动信息进行视频中字幕遮挡区域的恢复的方法.实验结果表明该方法取得了较好的视觉效果.     

一种适用于AVS-M的自适应快速运动估计算法

为了减小移动视频编码标准(AVS-M)中运动估计模块的复杂度,提出了一种快速、有效的块匹配运动估计算法.该算法充分利用了视频图像中运动矢量场的中心偏置特性和时空相关性,根据运动类型自适应的选择搜索起点和搜索策略,结合改进的搜索模板和高效搜索中止准则,有效地降低了运动估计的运算量.实验结果表明,该算法在保证搜索精度的同时,大大减少了搜索点数.     

基于邻域运动一致性的运动矢量快速构建算法

在时移电视应用中,视频快进播放要求视频服务器能够通过跳帧抽取视频序列中的I帧和P帧的方式输出快速播放码流,当所跳帧中含有P帧时,必需对抽取出来的快进码流中的P帧进行重编码.为提高抽取后重编码效率,可利用码流中的原始运动矢量对跳帧后新参考帧条件下的运动矢量进行预测.在FDVS和ADVS算法基础上,提出了一种基于宏块及其相邻宏块运动一致性的算法来修正原始运动矢量,并通过实验将其与现有的FDVS和ADVS算法进行比较.     

Content-Aware Fast Motion Estimation Algorithm

In this paper, we propose the Content-Aware Fast Motion Estimation Algorithm (CAFME) that can reduce computation complexity of motion estimation (ME) in H.264/AVC while maintaining almost the same coding efficiency. Motion estimation can be divided into two phases: searching phase and matching phase. In searching phase, we propose the Simple Dynamic Search Range Algorithm (SDSR) based on video characteristics to reduce the number of search points (SP). In matching phase, we integrate the Successive Elimination Algorithm (SEA) and the integral frame to develop a new SEA for H.264/AVC video compression standard, called Successive Elimination Algorithm with Integral Frame (SEAIF). Besides, we also propose the Early Termination Algorithm (ETA) to early terminate the motion estimation of current block.We implement the proposed algorithm in the reference software JM9.4 of H.264/AVC and the experimental results show that our proposed algorithm can reduce the number of search points about 93.1%, encoding time about 42%, while maintaining almost the same bitrate and PSNR.     

Neural fuzzy motion estimation and compensation

Neural fuzzy systems can improve motion estimation and compensation for video compression. Motion estimation and compensation are key parts of video compression. They help remove temporal redundancies in images. But most motion estimation algorithms neglect the strong temporal correlations of the motion field. The search windows stay the same through the image sequences and the estimation needs heavy computation. A neural vector quantizer system can use the temporal correlation of the motion field to estimate the motion vectors. First- and second-order statistics of the motion vectors give ellipsoidal search windows. This algorithm reduced the search area and entropy and gave clustered motion fields. Motion-compensated video coding further assumes that each block of pixels moves with uniform translational motion. This often does not hold and can produce block artifacts. We use a neural fuzzy system to compensate for the overlapped block motion. This fuzzy system uses the motion vectors of neighboring blocks to map the prior frame's pixel values to the current pixel value. The neural fuzzy system used 196 rules that came from the prior decoded frame. The fuzzy system learns and updates its rules as it decodes the image. The fuzzy system also improved the compensation accuracy. The paper derives both the fuzzy system and the neural learning laws that tune its parameters     

A Direction-Based Unsymmetrical-Cross Multi-Hexagon-Grid Search Algorithm for H.264/AVC Motion Estimation

The Unsymmetrical-cross Multi-hexagon-grid Search (UMHexagonS) is one of the best fast Motion Estimation (ME) algorithm in H.264/AVC (Advanced Video Coding) reference software. It achieves an excellent coding performance by using multiple initial search point predictors and hybrid block matching search pattern. However, the hybrid search pattern makes the computational complexity of ME increased. In this paper, we propose a Direction-based UMHexagonS (DBUMHexagonS) to further reduce the computational complexity of UMHexagonS. Each block matching search pattern of UMHexagonS is divided into four direction-based sub-search patterns, one of four directions is selected according to the difference between the Motion Vector (MV) of current block and the MV of its collocated block in previous frame, such a direction is applied to all following search patterns. As a result, the number of total search points will be dramatically reduced. Experimental results show that compared to the best UMHexagonS algorithm, the proposed algorithm can save the ME time up to 30.094 % while the rate-distortion performance is not compromised.     

Fast Multi-reference Motion Estimation via Enhanced Downhill Simplex Search

Block motion estimation can be regarded as a function minimization problem in a finite-dimensional space. Therefore, fast block motion estimation can be achieved by using an efficient function minimization algorithm instead of a predefined search pattern, such as diamond search. Downhill simplex search is an efficient derivative-free function minimization algorithm. In this paper, we proposed a fast block motion estimation algorithm based on applying the downhill simplex search for function minimization. Several enhanced schemes are proposed to improve the efficiency and accuracy, including a new initialization process, a special rounding scheme, and an early-stop error function evaluation procedure. We also extend the downhill simplex search for the multi-reference frame motion estimation problem. Experimental results show superior performance of the proposed algorithm over some existing fast block matching methods on several benchmarking video sequences.