Efficient search points reduction and ranking of Motion Estimation algorithms in video coding

Author(s):  
Md. Salah Uddin Yusuf ◽  
Mohiuddin Ahmad
2013 ◽  
Vol 756-759 ◽  
pp. 3455-3460
Author(s):  
Xiao Li Wang ◽  
Long Zhao

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.


2013 ◽  
Vol 21 (1) ◽  
Author(s):  
M. Jakubowski ◽  
G. Pastuszak

AbstractIn the multi-view video coding, both temporal and inter-view redundancies can be exploited by using standard block-based motion estimation (BBME) technique. In this paper, an extensive review of BBME algorithms proposed within the last three decades is presented. Algorithms are divided into five categories: 1) based on the search position number reduction; 2) multiresolution; 3) based on the simplification of matching criterion; 4) fast full search; 5) computation-aware. Algorithms are compared in terms of their efficiency and computational complexity.


2019 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
KUMAR VEMULA KIRAN ◽  
S. NEERAJA ◽  
◽  

2018 ◽  
Vol 7 (4.10) ◽  
pp. 928
Author(s):  
Prayline Rajabai C ◽  
Sivanantham S

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.  


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