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MATLAB implementation image sparse decomposition (matching pursuit with PSO optimization).

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MP2_DMS_PSO

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

Example

cameraman

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

[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

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

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MATLAB implementation image sparse decomposition (matching pursuit with PSO optimization).

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