Open AccessAN EFFICIENT MOTION ESTIMATION ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION
Author(s) -
Asha Elizabeth Jacob,
Immanuel Alex Pandian
Publication year - 2014
Publication title -
international journal of electronic signal and systems
Language(s) - English
Resource type - Journals
ISSN - 2231-5969
DOI - 10.47893/ijess.2014.1168
Subject(s) - motion estimation , block matching algorithm , computer science , algorithm , data compression , particle swarm optimization , search algorithm , computational complexity theory , motion compensation , quarter pixel motion , rate–distortion optimization , block (permutation group theory) , redundancy (engineering) , mathematical optimization , artificial intelligence , computer vision , video tracking , mathematics , video processing , geometry , operating system
The PSO algorithm reduce the search points without the degradation of the image quality. It provides accurate motion estimation with very low complexity in the context of video estimation. This algorithm is capable of reducing the computational complexity of block matching process. This algorithm maintains high estimation accuracy compared to the full search method. The critical component in most block-based video compression system is Motion Estimation because redundancy between successive frames of video sequence allows for compression of video data. These algorithms are used to reduce the computational requirement by checking only some points inside the search window, while keeping a good error performance when compared with Full Search and Diamond search algorithm. This algorithm should maintain high estimation accuracy compared to the Full search method and Diamond search algorithm. Here by using the PSO algorithm could get a high accuracy in the block-based motion estimation.