Infrared and visual image registration based on mutual information with a combined particle swarm optimization – Powell search algorithm

Optik ◽  
2016 ◽  
Vol 127 (1) ◽  
pp. 188-191 ◽  
Author(s):  
Youwen Zhuang ◽  
Kun Gao ◽  
Xianghu Miu ◽  
Lu Han ◽  
Xuemei Gong
Keyword(s):  
Particle Swarm Optimization ◽  
Image Registration ◽  
Mutual Information ◽  
Search Algorithm ◽  
Particle Swarm ◽  
Visual Image ◽  
Swarm Optimization

Image Registration Based on MI and PSO Algorithm

2011 ◽  
Vol 267 ◽  
pp. 569-573
Author(s):  
Jun Hong Xu ◽  
Jin Li ◽  
Yan Wei Wang ◽  
Hong Liang ◽  
Dong Chao Tian ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Image Registration ◽  
Mutual Information ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
New Method ◽  
Swarm Optimization

To improve the performance of image registration technology, a new method based on mutual information and PSO (Particle swarm optimization) is proposed in this paper. The MI (mutual Information) algorithm has been applied on image registration. The PSO algorithm is used to find the maximum MI. Compared the PSO and the POWELL algorithms, the results show that the PSO algorithm performs fairly well compared with the traditional algorithms.

Localization of WSN using Distributed Particle Swarm Optimization algorithm with precise references

2016 ◽  
Vol 7 ◽  
pp. 1
Author(s):  
Ravichander Janapati ◽  
Ch. Balaswamy ◽  
K. Soundararajan
Keyword(s):  
Particle Swarm Optimization ◽  
Search Algorithm ◽  
Particle Swarm ◽  
Search Space ◽  
Research Area ◽  
Population Based ◽  
Wireless Sensor ◽  
Cooperative Localization ◽  
Localization Algorithm ◽  
Swarm Optimization

Localization is the key research area in wireless sensor networks. Finding the exact position of the node is known as localization. Different algorithms have been proposed. Here we consider a cooperative localization algorithm with censoring schemes using Crammer Rao bound (CRB). This censoring scheme  can improve the positioning accuracy and reduces computation complexity, traffic and latency. Particle swarm optimization (PSO) is a population based search algorithm based on the swarm intelligence like social behavior of birds, bees or a school of fishes. To improve the algorithm efficiency and localization precision, this paper presents an objective function based on the normal distribution of ranging error and a method of obtaining the search space of particles. In this paper  Distributed localization of wireless sensor networksis proposed using PSO with best censoring technique using CRB. Proposed method shows better results in terms of position accuracy, latency and complexity.  

scholarly journals Software Defects Prediction Based on Hybrid Particle Swarm Optimization and Sparrow Search Algorithm

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 60865-60879
Author(s):  
Liu Yang ◽  
Zhen Li ◽  
Dongsheng Wang ◽  
Hong Miao ◽  
Zhaobin Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Search Algorithm ◽  
Particle Swarm ◽  
Software Defects ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hybrid Particle Swarm Optimization
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