Improvements on Motion Estimation Algorithms in Video Coding for H.264/AVC

2013 ◽  
Vol 756-759 ◽  
pp. 3455-3460
Author(s):  
Xiao Li Wang ◽  
Long Zhao
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Real Time ◽  
Video Compression ◽  
Motion Vector ◽  
Coding Efficiency ◽  
Estimation Algorithms ◽  
Whole Process ◽  
Motion Activity ◽  
Precision Motion

Motion estimation is the most important step in video compression. By using high precision motion vector in the H.264 encoder, the calculation is rapidly increased, but in the whole process of coding, motion estimation occupies about 80%. Although many motion estimation algorithms have been proposed to reduce the computational complexity of motion estimation, it still cannot meet the strict real-time demand. In this paper, based on the analysis of UMHexagonS algorithm, dynamic searching window is chosen in the UMHexagonS algorithm, then according to the motion activity, it uses different template to reduce the motion estimation time and improve video coding efficiency. Proved by the experiments on various test sequences, compared with the UMHexagonS algorithm, the motion estimation time of the proposed algorithm average saves 17.7525% in the case of the quality of the reconstructed image and rate close. It not only reduces the complexity of the algorithm, but also improves the real-time performance of the encoder.

An Improved Approach of Block Matching Algorithm for Motion Vector Estimation

2018 ◽  
Vol 8 (1) ◽  
pp. 38-56 ◽  
Author(s):  
Shailesh D. Kamble ◽  
Sonam T. Khawase ◽  
Nileshsingh V. Thakur ◽  
Akshay V. Patharkar
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
Motion Vector ◽  
Real Life ◽  
Computation Time ◽  
Block Matching ◽  
Video Encoding ◽  
Compression Technique ◽  
Block Matching Algorithm ◽  
Estimation Algorithms

Motion estimation has traditionally been used in video encoding only, however, it can also be used to solve various real-life problems. Nowadays, researchers from different fields are turning towards motion estimation. Motion estimation has become a serious problem in many video applications. It is a very important part of video compression technique and it provides improved bit rate reduction and coding efficiency. The process of motion estimation is used to improve compression quality and it also reduces computation time. Block-based motion estimation algorithms are used as they require less memory for processing of any video file. It also reduces the complexity involved in computations. In this article, various block-matching motion estimation algorithms are discussed such as Full search (FS) or Exhaust Search, Three-Step search (TSS), New Three-Step search (NTSS), Four-Step search (FSS), Diamond search (DS) etc.

scholarly journals Review on Architectures of Motion Estimation for Video Coding Standards

2018 ◽  
Vol 7 (4.10) ◽  
pp. 928
Author(s):  
Prayline Rajabai C ◽  
Sivanantham S
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Video Compression ◽  
Video Data ◽  
Video Codec ◽  
Current Frame ◽  
Estimation Algorithms ◽  
Hardware Architectures ◽  
Coding Standards ◽  
Extensive Computation

Various video coding standards like H.264 and H.265 are used for video compression and decompression. These coding standards use multiple modules to perform video compression. Motion Estimation (ME) is one of the critical blocks in the video codec which requires extensive computation. Hence it is computationally complex, it critically consumes a massive amount of time to process the video data. Motion Estimation is the process which improves the compression efficiency of these coding standards by determining the minimum distortion between the current frame and the reference frame. For the past two decades, various Motion Estimation algorithms are implemented in hardware and research is still going on for realizing an optimized hardware solution for this critical module. Efficient implementation of ME in hardware is essential for high-resolution video applications such as HDTV to increase the decoding throughput and to achieve high compression ratio. A review and analysis of various hardware architectures of ME used for H.264 and H.265 coding standards is presented in this paper.  

Modified TZ Search Method for Motion Estimation in Multi-View Video Coding

2013 ◽  
Vol 717 ◽  
pp. 754-759
Author(s):  
Hyo Sun Yoon ◽  
Mi Young Kim
Keyword(s):  
Computational Complexity ◽  
Image Quality ◽  
Motion Estimation ◽  
Video Coding ◽  
Video Compression ◽  
Motion Vector ◽  
Three Dimensional ◽  
Search Method ◽  
Optimal Motion ◽  
Quality Degradation

Motion estimation (ME) plays an important role in digital video compression. But it requires huge complexity to find an optimal motion vector. Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. The computational complexity for motion estimation in multi view video coding increases in proportion to the number of cameras. To reduce computational complexity and maintain the image quality, a modified TZ search method for motion estimation in multi-view video coding is proposed in this paper. The proposed search method exploits the characteristics of the distribution of motion vectors to place the search points. Experiment results show that the speedup improvement of the proposed method over Pel Block Search and TZ search method (JMVC) can be up to more than 77 times and 1.8 ~4.5 times faster respectively by reducing the computational complexity and the image quality degradation is about to 0.05 ~ 1(dB) and 0.010.24 (dB) respectively.

Adaptive Return Prediction Block Matching Algorithms for Video Coding

2011 ◽  
Vol 145 ◽  
pp. 277-281
Author(s):  
Vaci Istanda ◽  
Tsong Yi Chen ◽  
Wan Chun Lee ◽  
Yuan Chen Liu ◽  
Wen Yen Chen
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
Web Site ◽  
Motion Vector ◽  
Temporal Correlation ◽  
Block Matching ◽  
Asynchronous Learning ◽  
Learning And Teaching ◽  
Block Motion ◽  
Reconstruction Image

As the development of network learning, video compression is important for both data transmission and storage, especially in a digit channel. In this paper, we present the return prediction search (RPS) algorithm for block motion estimation. The proposed algorithm exploits the temporal correlation and characteristic of returning origin to obtain one or two predictive motion vector and selects one motion vector, which presents better result, to be the initial search center. In addition, we utilize the center-biased block matching algorithms to refine the final motion vector. Moreover, we used adaptive threshold technique to reduce the computational complexity in motion estimation. Experimental results show that RPS algorithm combined with 4SS, BBGDS, and UCBDS effectively improves the performance in terms of mean-square error measure with less average searching points. On the other hand, accelerated RPS (ARPS) algorithm takes only 38% of the searching computations than 3SS algorithm, and the reconstruction image quality of the ARPS algorithm is superior to 3SS algorithm about 0.30dB in average overall test sequences. In addition, we create an asynchronous learning environment which provides students and instructors flexibility in learning and teaching activities. The purpose of this web site is to teach and display our researchable results. Therefore, we believe this web site is one of the keys to help the modern student achieve mastery of complex Motion Estimation.

Fast Motion Estimation Algorithm Based on Real Time Monitoring

2011 ◽  
Vol 383-390 ◽  
pp. 5028-5033
Author(s):  
Xue Mei Xu ◽  
Qin Mo ◽  
Lan Ni ◽  
Qiao Yun Guo ◽  
An Li
Keyword(s):  
Motion Estimation ◽  
Real Time ◽  
Computation Time ◽  
Estimation Algorithm ◽  
Video Encoding ◽  
Experimental Result ◽  
Fast Motion Estimation ◽  
Motion Activity ◽  
Search Patterns ◽  
Motion Estimation Algorithm

In the video encoding system, motion estimation plays an important role at the front-end of encoder, which can eliminate inter redundancy efficiently and improve encoding efficiency. However, traditional motion estimation algorithm can’t be used in real-time application like video monitoring due to its computational complexity. In order to improve real-time efficiency, an improved motion estimation algorithm is proposed in this paper. The essential ideas consist of early termination rules, prediction of initial search point, and determination of motion type. Furthermore, our algorithm adopts different search patterns for certain motion activity. Experimental result shows that the improved algorithm reduces the computation time significantly while maintaining the image quality, and satisfies real time requirement in monitoring system.

scholarly journals Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

2020 ◽  
Vol 34 (07) ◽  
pp. 11580-11587
Author(s):  
Haojie Liu ◽  
Han Shen ◽  
Lichao Huang ◽  
Ming Lu ◽  
Tong Chen ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Temporal Correlation ◽  
Second Order ◽  
Compression Method ◽  
High Efficiency Video Coding ◽  
First Order ◽  
Coding Efficiency ◽  
The Common

Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role in video coding. Thus, in this paper, we propose to exploit the temporal correlation using both first-order optical flow and second-order flow prediction. We suggest an one-stage learning approach to encapsulate flow as quantized features from consecutive frames which is then entropy coded with adaptive contexts conditioned on joint spatial-temporal priors to exploit second-order correlations. Joint priors are embedded in autoregressive spatial neighbors, co-located hyper elements and temporal neighbors using ConvLSTM recurrently. We evaluate our approach for the low-delay scenario with High-Efficiency Video Coding (H.265/HEVC), H.264/AVC and another learned video compression method, following the common test settings. Our work offers the state-of-the-art performance, with consistent gains across all popular test sequences.

A coprocessor for real-time motion estimation in HD video coding

2010 ◽  
Author(s):  
Huitao Gu ◽  
Shuwei Sun ◽  
Shuming Chen
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Real Time ◽  
Time Motion

scholarly journals A Fast Fractal Video Coding Algorithm Using Cross-Hexagon Search for Block Motion Estimation

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Kamel Belloulata ◽  
Shiping Zhu ◽  
Zaikuo Wang
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Search Algorithm ◽  
Motion Vector ◽  
Block Matching ◽  
Block Motion ◽  
Search Patterns ◽  
Vector Distribution ◽  
Search Speed ◽  
Block Motion Estimation

We propose a novel fractal video coding method using fast block-matching motion estimation to overcome the drawback of the time-consuming character in the fractal coding. As fractal encoding essentially spends most time on the search for the best-matching block in a large domain pool, search patterns and the center-biased characteristics of motion vector distribution have large impact on both search speed and quality of block motion estimation. In this paper, firstly, we propose a new hexagon search algorithm (NHEXS), and, secondly, we ameliorate, by using this NHEXS, the traditional CPM/NCIM, which is based on Fisher's quadtree partition. This NHEXS uses two cross-shaped search patterns as the first two initial steps and large/small hexagon-shaped patterns as the subsequent steps for fast block motion estimation (BME). NHEXS employs halfway stop technique to achieve significant speedup on sequences with stationary and quasistationary blocks. To further reduce the computational complexity, NHEXS employs modified partial distortion criterion (MPDC). Experimental results indicate that the proposed algorithm spends less encoding time and achieves higher compression ratio and compression quality compared with the traditional CPM/NCIM method.

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