A reconstructed algorithm based on QPSO in compressed sensing

In compressed sensing (CS), the orthogonal matching pursuit (OMP) algorithm is considered as a typical reconstructed algorithm. But, it needs a great amount of calculations to reconstruct the original signal. In order to reduce the OMP algorithm computational complexity, we proposed the improved reconstruction algorithm, which combines with quantum-behaved particle swarm (QPSO) algorithm and OMP algorithm to reconstructed image with low complexity and the better safety performance. The simulation results show that the QPSO&OMP algorithm has the better effect on reconstructed image when the value of M is taken smaller. And it has better stability and fast convergence ability for image processing.