Atomic Decomposition by Basis Pursuit
SIAM Review
Journal of Global Optimization
Efficient image representation by anisotropic refinement in matching pursuit
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
A Cooperative approach to particle swarm optimization
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
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In this paper, with projection value being considered as fitness value, the Dynamic Multi-Swarm Particle Swarm Optimizer (DMS-PSO) is applied to improve the best atom searching problem in the Sparse Decomposition of image based on the Matching Pursuit (MP) algorithm. Furthermore, Discrete Coefficient Mutation (DCM) strategy is introduced to enhance the local searching ability of DMS-PSO in the MP approach over the anisotropic atom dictionary. Experimental results indicate the superiority of DMS-PSO with DCM strategy in contrast with other popular versions of PSO.