Fast Motion Estimation Algorithm Research Articles

Hardware motion estimation methods survey and example real-time architecture design

Motion estimation is essential in video processing, computer vision, and other related fields due to its applications in improving data compression, enhancing image/video quality, increasing computer vision task accuracy, and conserving computational resources. Typical motion estimation methods include FS (Full Search) and DS (Diamond Search). Traditional motion estimation methods will face the challenge of high complexity in practical real-time applications. Therefore, this paper focuses on fast motion estimation algorithms and hardware architecture design for real-time applications survey and research. Aiming at the need for 1920x1080@60fps processing speed, this paper explores the key ideas of FS and DS hardware structure design based on the Vivado HLS high-level synthesis tool and provides a feasible hardware scheme to meet the real-time requirements.

Motion estimation algorithm and architecture survey

Motion estimation is a key part of video temporal characteristics analysis including video filter and compression. Increasing requirements for high-quality video image processing have confirmed the necessity of researching motion estimation. Current motion estimation methods, including high-efficient fast motion estimation algorithms and hardware architecture designs, achieved different performances from different perspectives. In this paper, we focus on analyzing typical fast algorithms and hardware architecture designs for motion estimation, comparing the used methods, and pointing out the basic ideas of motion estimation research schemes. In terms of theoretical implications, the research contributed to a more comprehensive reference for fast motion estimation algorithms and their hardware architecture designs.

Test Zone Search Optimization Using Cuckoo Search Algorithm for VVC

Motion vector approximation is an integral part of every video coding standard to reduce temporal correlation. Estimating motion necessitates a lot of computation. Several attempts were made to reduce the computation cost in exhaustive search of motion estimation. Test zone search was accepted as benchmark algorithm for fast motion estimation by the most recent video coding standard, versatile video coding. Quality and speed of test zone search completely depends on two parameters (i.e., sub sampling frequency of search space during raster scan and dimension of the search space). Cuckoo search, one of the popular nature-inspired optimization algorithms, is used to optimize the operational parameters of test zone search. The proposed optimization enhanced the speed up to 50% while maintaining or improving the Bjontegaard rate (BD-Rate) and Bjontegaard PSNR (BDSNR).

Learning-based bypass zone search algorithm for fast motion estimation

Learning-based bypass zone search algorithm for fast motion estimation

A fast partial distortion-based motion estimation algorithm in Walsh–Hadamard domain

A fast partial distortion-based motion estimation algorithm in Walsh–Hadamard domain

An Improved Fast Motion Estimation Algorithm in H.266/VVC

Motion estimation is a key technique of video compression coding, H.266/VVC (Versatile Video Coding) inter TZsearch fast motion estimation algorithm using the diamond search model, although the search model matching precision is high, but because of the number of search points need to match, so the computational complexity is higher also, for this defect, the article on the basis of the standard algorithm, The fast algorithm of TZSearch is optimized and improved. Firstly, the hexagonal search model with excellent performance and speed is used to replace the diamond search model in the standard algorithm. Secondly, on the basis of the rotation hexagon model, the number of initial matching search points of the rotation hexagon search model is further increased by using the feature of natural video prediction MV center bias. At the same time, a reasonable early termination threshold is set for the whole motion estimation process. Simulation results show that compared with VTM14.0 standard algorithm, the proposed algorithm reduces BDBR by 0.17% and BDPSNR by 0.04dB on average, and the overall coding time is saved by 48.85% on average. The proposed algorithm can effectively reduce the computational complexity of motion estimation process on the premise of guaranteeing the coding quality.

Efficient fast motion estimation algorithm for real-time applications

Efficient fast motion estimation algorithm for real-time applications

Correction to: Efficient fast motion estimation algorithm for real-time applications

Correction to: Efficient fast motion estimation algorithm for real-time applications

A very fast edge map-based algorithm for accurate motion estimation

Motion estimation plays a very crucial role in many video applications. Hence, an accurate and fast algorithm is required in real-time applications. Although exhaustive block matching (EBM) algorithm is the best algorithm used for motion estimation in terms of performance, it is computationally very expensive. Several algorithms have been developed in the literature to reduce the computational time required by the EBM algorithm; however, their performance is not comparable to that of EBM. In this paper, we propose an extremely fast technique for motion estimation based on the edge map of only a fraction of the frame. Extensive experiments are carried out, and the results show that the proposed technique provides a performance comparable to that of the EBM algorithm, with a very low computational complexity.

One-dimensional Block Matching Algorithm in Video Image Motion Estimation

<p indent=0mm>Motion estimation is a basic problem in the fields of video image compression and video image restoration. The traditional block matching methods have good search quality, but the search speed is not fast enough. Aiming at the shortcomings of the search speed in the traditional block matching methods, we proposed a fast one-dimensional block matching motion estimation algorithm. Firstly, the motion vector is orthogonally decomposed, and the two-dimensional matching block is reduced by a special weight coefficient matrix to obtain two sets of one-dimensional feature matrices. Then the one-dimensional three step search method is selected as the search strategy. The sum of absolute differences criterion is used as the matching criterion. The two sets of one-dimensional feature matrices are used to search for the two components of the matching motion vector. Finally the two components are formed into a complete motion vector. The results of multiple sets of comparative experiments show that the search speed of motion estimation is significantly improved while the algorithm is guaranteed to quantitatively evaluate the PSNR. The higher the video definition and the larger the pixel size of the matching block, the better the algorithm can improve the search speed of motion estimation.

WITHDRAWN: Developing new search pattern in fast motion estimation algorithm used for compress a video

Due to rapid growing of digital video, it was very complicated task for storing, processing and transferring a sequence of video. Motion Estimation (ME) is a primary tool for video compression. This paper comprises new pattern i.e. rectangular search pattern used in place of diamond search pattern in block-based motion estimation algorithm. The performance can be measured in terms of number of points searching in searching area per macro-block and quality of video by using PSNR value.

Dynamically Adaptive Fast Motion Estimation Algorithm for HD Video

This paper presents a novel adaptive Fast Motion Estimation (FME) Algorithm, which reduces the number of search points, computational complexity and therefore lowering power consumption, while providing improved quality per watt in FME. The algorithm minimizes computation and storage and from there, power consumption, while trying to preserve quality as much as possible. It is very suitable for hardware implementation, as in a motion co-processor. The pervasiveness of mobile devices with HD video capabilities demands such low power hardware accelerators. The proposed algorithm is a novel method, that can identify the best search pattern within a given region of the HD video frame, based on its motion dynamics to achieve lower power video encoding. The goal is to achieve the best quality with the minimum number of search iterations. The reduced number of checks translates into power savings. The motivation of the presented algorithm is to learn the motion dynamics within a region from a small subset of blocks within that region and apply that knowledge to the remaining large set of blocks in the same region. This adaptiveness makes it robust with respect to the nature of the video. Thus it works equally well with more dynamic and with less dynamic video sequences. The results show that the proposed algorithm can reduce computations by about 4 times compared to other fixed search patterns algorithms, while staying within 1 dB of PSNR results. That equates to about 75% power savings at the expense of not more than 1 dB of PSNR quality loss.

An efficient algorithm for fast block matching motion estimation using an adaptive threshold scheme

A new block-matching algorithm for fast motion estimation is proposed. The so-called Star Diamond Search with Adaptive Threshold (SDth) is two steps algorithm. Adaptive threshold for matching errors eliminates invalid blocks early from motion estimation procedure. Then it performs a search for final motion vector with a Star Diamond Algorithm. Proposed SDth algorithm has been implemented and tested using several video sequences. SDth algorithm is also compared with previous search methods to demonstrate its utility.

Complexity reduction of test zonal search for fast motion estimation in uni-prediction of High Efficiency Video Coding

The complexity of motion estimation in the High Efficiency Video Coding (HEVC) standard is very high as it uses a number of prediction block sizes. The test zonal search (TZS) mechanism is used as motion estimation algorithm in the fast search mode of HM encoder, the reference software for HEVC. In this paper, we present schemes for reducing the complexity of the TZS algorithm for uni-prediction in HEVC. The proposed mechanisms help in reducing complexity of grid, raster and refinement search stages of TZS. The performance of the proposed mechanisms is tested independently and also combined in the fast search mode of HM-16.18. The motion estimation time and the number of search points in the combined algorithm are reduced by 68.14% and 77.10% with a BD-rate of 0.30% and a BD-PSNR of $$-0.007$$ dB in comparison with the original fast search mode in the low-delay P main profile. The proposed complexity reduction schemes are compared with those adopted in other recently proposed fast motion estimation algorithms and the performance of the proposed scheme is found to be superior in terms of the reduction in motion estimation time.

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.

A low complexity and computationally scalable fast motion estimation algorithm for HEVC

Motion Estimation (ME) is one of the most computationally demanding parts of video encoders. The Test Zone (TZ) search is a popular fast ME algorithm, which is recommended for High-Efficiency Video Coding (HEVC). While the TZ search achieves an excellent coding efficiency, it is not a favorable choice for hardware implementations due to 1) a relatively high computational complexity, 2) inducing data dependency among the neighboring blocks, which complicates hardware implementations and parallel processing in software implementations, and 3) lack of computational adjustability, which is required for video encoding in power-constrained devices. This paper diagnoses the cause of these issues to be in the multiple starting search points of the TZ search algorithm. Accordingly, a method is proposed to find a single reliable starting point that replaces the first step of the TZ search algorithm. To do so, both current and reference frames are analyzed using a complex wavelet transform, and similar salient points are identified among the two frames. Then a light-weight process is used to match these points to find a single reliable starting point. The reliability of this point leads to reduced zonal refinement range with negligible cost in compression efficiency. Since adjusting the refinement range can be used as an effective way for adjusting the complexity, this results in a computationally scalable ME algorithm, named FMECWT. In contrast to the existing methods, FMECWT does not rely on neighboring blocks, which eliminates the inherent data dependency of TZ search. Experimental results show that FMECWT achieves ~35% to ~85% ME time reduction compared to TZ search, with only 0.1% to 1.7% increase in BD-Rate.

Improved motion estimation algorithm based on integrity index and its implementation in x265

With the development of fast motion estimation (ME) algorithms towards video compression standard H.264, burden on integer-pel ME is slightly reduced. However the integer-pel ME is becoming computationally complex due to demand of higher and higher resolution videos. On the other hand, there is always trade-off between the speed and performance of these search algorithms. This work improvises the performance of content awareness enabled integer-pel ME algorithm for encoding the fast and slow motion video sequences of high definition (HD) resolution category viz. 1280×720 and 1920×1080. The algorithm proposes a novel notion of 'integrity index' with focus on increasing the PSNR and reducing the bit rate. It is implemented in the frame work of x265 version 1.7 video encoder. Motion independent ME algorithm is analysed quantitatively in terms of parameters based on rate distortion and ME time. The proposed algorithm is found to be performing better on BD-Rate and BD-PSNR parameters for the videos of both resolutions under consideration. Observed increase in motion estimation time is less than four seconds compared to hexagonal search algorithm of ME which is the benchmark in fast ME algorithm.

Fast global motion estimation on single instruction multiple data processors for real-time devices

Global motion estimation is a fundamental tool for image processing and computer vision. Since low-cost real-time devices have limited computational resources, the computational burden of global motion estimation remains considerable for low-cost devices. Hence, a fast global motion estimation algorithm for single instruction multiple data (SIMD) processors with which a CPU in modern mobile computing devices is commonly equipped is proposed. Conventional projection-based global motion estimation is modified to improve the prediction accuracy for videos containing large motions. To significantly increase the parallelism, the exact sizes of the variables in each processing step of the proposed algorithm are determined by considering the size of an SIMD register. Simulation results demonstrate that the proposed scheme is considerably fast and accurate, even for videos containing large motions.

Fast hierarchical wavelet-domain motion estimation for arbitrarily shaped visual objects

Motion estimation is widely used for video compression as it reduces the memory requirements of any video file while maintaining high visual quality. But the computational cost consumed by motion estimation/compensation usually accounts for more than 50%, even to 80%, of the total cost of the encoder. So researchers try to develop fast motion estimation algorithms to lower the computational complexity. Moreover, few studies have been concentrated on the efficient motion estimation of arbitrarily shaped visual objects, which particularly pays insufficient attention to boundary continuity of the motion-compensated objects as well. In this research, we present a hierarchical wavelet-domain approach to motion estimation of visual objects with arbitrary shapes. We explore the guiding role of binary alpha-plane in assisting motion estimation of visual objects, and bring forward a binary alpha-plane matching scheme. It constrains the intensity-based motion estimation into a small subset of initial candidate vectors in the search window. This both accelerates search speed and helps to produce coherent object boundary. Moreover, we employ the low-band-shift technique to eliminate the wavelet’s shift-variance effect. And based on the observation that high frequency subbands of wavelet contribute little to calculating motion vectors, a new matching function is derived for fast wavelet-domain motion estimation. Coupled with the alpha-plane matching and the devised matching function, a hierarchical low-band-based motion estimation approach is further proposed. Through executing a refined search around the initial candidate vectors using only the low frequency subband at each scale, our approach achieves a satisfying balance between prediction accuracy and computational efficiency. Experimental results show that by using the standard accuracy measurements and the benchmark video sequences, the performance of the proposed approach is close to the full search with a matching quality over 99%, and with 95.80% reduction in complexity.

Fast motion estimation algorithm based on geometric wavelet transform

Motion estimation is a means, which consists in studying the displacement of objects in a video sequence, seeking the correlation between two successive frames, to predict the change in the contents position. Motion estimation is becoming a progressively significant requirement in a variety of applications such as medicine, robotics and video compression. In recent years, wavelets are effective tools for motion estimation, but the DWT (Discrete Wavelet Transform) will suffer from problems like translation sensitivity, poor directionality and absence of phase information. These three disadvantages make classical wavelets incapable of calculating motion in complex sequences (contain several directions.). In order to improve these negative aspects, we will choose geometric wavelet. Therefore, our objective is to propose a method capable of estimating the motion in terms of performance (speed and accuracy). This method will be based on the geometric wavelet transform and more precisely on the Contourlet transform. This work consists of two parts: in the first stage, the denoising process is examined by the Contourlet transform to ensure the precision of motion; in the second phase, we applied the iterative method of Horn and Schunck to calculate the motion in order to guarantee good speed. Comparative experimental results of artificial sequences show that the proposed algorithm obtains considerably better performance than several state-of-the-art methods.