Multilevel thresholding based on CDPSO

Version 1.0.0 (777 KB) by Shilpa Suresh

An improved variant of Darwinian PSO algorithm based on chaotic functions.

https://github.com/ShilpaSuresh89/codes

0.0

(0)

179 Downloads

Updated 16 Jul 2019

View License on GitHub

An improved variant of Darwinian PSO algorithm based on chaotic functions.
It replaces random sequences by chaotic sequences mitigating the problem of premature convergence.Efficiency of 10 defined chaotic maps are investigated and the best one was chosen.

Cite As

Suresh, Shilpa, and Shyam Lal. “Multilevel Thresholding Based on Chaotic Darwinian Particle Swarm Optimization for Segmentation of Satellite Images.” Applied Soft Computing, vol. 55, Elsevier BV, June 2017, pp. 503–22, doi:10.1016/j.asoc.2017.02.005.

View more styles

MATLAB Release Compatibility

Created with R2019a

Compatible with any release

Platform Compatibility

Windows macOS Linux

Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versions that use the GitHub default branch cannot be downloaded

Version	Published	Release Notes
1.0.0	16 Jul 2019

To view or report issues in this GitHub add-on, visit the GitHub Repository.

MLA	Suresh, Shilpa, and Shyam Lal. “Multilevel Thresholding Based on Chaotic Darwinian Particle Swarm Optimization for Segmentation of Satellite Images.” Applied Soft Computing, vol. 55, Elsevier BV, June 2017, pp. 503–22, doi:10.1016/j.asoc.2017.02.005.
APA	Suresh, S., & Lal, S. (2017). Multilevel thresholding based on Chaotic Darwinian Particle Swarm Optimization for segmentation of satellite images. Applied Soft Computing, 55, 503–522. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.asoc.2017.02.005
BibTeX	@article{Suresh_2017, doi = {10.1016/j.asoc.2017.02.005}, url = {https://doi.org/10.1016%2Fj.asoc.2017.02.005}, year = 2017, month = {jun}, publisher = {Elsevier {BV}}, volume = {55}, pages = {503--522}, author = {Shilpa Suresh and Shyam Lal}, title = {Multilevel thresholding based on Chaotic Darwinian Particle Swarm Optimization for segmentation of satellite images}, journal = {Applied Soft Computing} }