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 A Three-Point Directional Search Block Matching Algorithm

2017 ◽  
Vol 7 (1) ◽  
pp. 230 ◽  
Author(s):  
A.V. Paramkusam ◽  
D. Laxma Reddy
Keyword(s):  
Motion Estimation ◽  
Motion Vector ◽  
Block Matching ◽  
Search Pattern ◽  
Fast Search ◽  
Block Matching Algorithm ◽  
Estimation Algorithms ◽  
Search Patterns ◽  
Search Speed ◽  
Minimum Block

<p>This paper proposes compact directional asymmetric search patterns, which we have named as three-point directional search (TDS). In most fast search motion estimation algorithms, a symmetric search pattern is usually set at the minimum block distortion point at each step of the search. The design of the symmetrical pattern in these algorithms relies primarily on the assumption that the direction of convergence is equally alike in each direction with respect to the search center. Therefore, the monotonic property of real-world video sequences is not properly used by these algorithms. The strategy of TDS is to keep searching for the minimum block distortion point in the most probable directions, unlike the previous fast search motion estimation algorithms where all the directions are checked. Therefore, the proposed method significantly reduces the number of search points for locating a motion vector. Compared to conventional fast algorithms, the proposed method has the fastest search speed and most satisfactory PSNR values for all test sequences.</p>

An Efficient Algorithm for Fast Block Motion Estimation in High Efficiency Video Coding

2016 ◽  
pp. 132-150
Author(s):  
Murugesan Ezhilarasan ◽  
Kumar K. Nirmal ◽  
P. Thambidurai
Keyword(s):  
Motion Estimation ◽  
High Efficiency ◽  
Search Time ◽  
Temporal Correlation ◽  
Block Matching ◽  
Video Encoding ◽  
Computational Time ◽  
High Efficiency Video Coding ◽  
Block Matching Algorithm ◽  
Estimation Algorithms

The Motion Estimation is an indispensable module in the design of video encoder. It employs Block Matching algorithm which involves searching a candidate block in the entire search window of the reference frame taking up to 80% of the total video encoding time. In order to increase the efficiency, several Block Matching Algorithms are employed to minimize the computational time involved in block matching. The chapter throws light on an efficient approach to be applied to the existing Block Matching Search techniques in HEVC which outperforms the various Block Matching algorithms. It involves two steps namely – Prediction and Refinement. The prediction step considers two parameters such as the temporal correlation and the direction to predict the MV of the candidate block. Several combinations of the search points are formulated in the refinement step of the algorithm to minimize the search time. The results depict that the Efficient Motion Estimation schemes provide a faster search minimizing the computational time upon comparison with the existing Motion Estimation algorithms.

scholarly journals A New Block Matching Algorithm for Motion Estimation

2016 ◽  
Vol 855 ◽  
pp. 178-183 ◽  
Author(s):  
Chia Ming Wu ◽  
Jen Yi Huang
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
Motion Compensation ◽  
Video Processing ◽  
Motion Vector ◽  
Block Matching ◽  
Matching Algorithm ◽  
Block Matching Algorithm ◽  
Fast Motion ◽  
Better Than

Motion estimation has been the most key role on video processing. It is usually applied to block matching algorithm for choosing the best motion vector. The two adjacent images are searched to find the displacement of the same object in the video image. Many fast motion vector block matching algorithms are proposed, and they achieve the efficiency of motion compensation and video compression. In our paper, we propose a new algorithm that is based on ARPS. The experimental results show that the PSNR of the proposed method is better than that of other block matching methods on many kinds of video.

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.

Sign in / Sign up

Export Citation Format

Share Document