# MP2_DMS_PSO

**Repository Path**: weirdochen/MP2_DMS_PSO

## Basic Information

- **Project Name**: MP2_DMS_PSO
- **Description**: MATLAB implementation image sparse decomposition (matching pursuit with PSO optimization).
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-07-16
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# MP2_DMS_PSO
MATLAB implementation of the image sparse decomposition algorithm (based on matching pursuit with PSO optimization).

## Example
![cameraman](./cameraman.png)


## References: 
[1] [C. Chen, J.J. Liang, B.Y. Qu, and B. Niu, "Using Dynamic Multi-Swarm Particle Swarm Optimizer to Improve the Image Sparse Decomposition Based on Matching Pursuit," ICIC 2013, LNAI 7996, pp. 587–595, 2013](https://link.springer.com/chapter/10.1007/978-3-642-39482-9_68)

[2] [Liang, J.J.; Suganthan, P.N., "Dynamic multi-swarm particle swarm optimizer," Swarm Intelligence Symposium, 2005. SIS 2005. Proceedings 2005 IEEE , vol., no., pp.124,129, 8-10 June 2005, doi: 10.1109/SIS.2005.1501611](https://ieeexplore.ieee.org/document/1501611/)

## Citation
Chen C., Liang J.J., Qu B.Y., Niu B. (2013) Using Dynamic Multi-Swarm Particle Swarm Optimizer to Improve the Image Sparse Decomposition Based on Matching Pursuit. In: Huang DS., Jo KH., Zhou YQ., Han K. (eds) Intelligent Computing Theories and Technology. ICIC 2013. Lecture Notes in Computer Science, vol 7996. Springer, Berlin, Heidelberg