Title :
An Improved Particle Swarm Optimization Algorithm for Image Matching
Author :
Ru, An ; Chunye, Chen ; Huilin, Wang
Author_Institution :
Dept. of Geogr. Inf. Sci., Hohai Univ., Nanjing, China
Abstract :
Image matching is widely applied in the areas of pattern recognition, computer vision, medicine, remote sensing, aircraft navigation and movement tracking. In this paper, an improved particle swarm optimization algorithm based on variable swarm population size and mutual information as similarity measure function is proposed for image matching. The aim is to enhance the overall performance of image matching. The proposed scheme adjusts the population size in terms of the diversity of the population. The algorithm presented is compared with the exhaustive search based on mutual information, and standard PSO. Remote sensing images captured by different sensors with different resolutions are as testing data. It is proved that the algorithm the paper suggested is effective for image matching.
Keywords :
image matching; particle swarm optimisation; image matching; mutual information; particle swarm optimization; population diversity; remote sensing image; similarity measure function; variable swarm population size; Aircraft navigation; Biomedical imaging; Computer vision; Image matching; Mutual information; Particle measurements; Particle swarm optimization; Pattern recognition; Remote sensing; Tracking; image matching; image registration; mutual information; particle swarm optimization; variable swarm population size;
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
DOI :
10.1109/IFCSTA.2009.8
