A hybrid hard thresholding algorithm for compressed sensing

Iterative hard thresholding algorithm (IHT) is a novel and efficient method to solve signal and image reconstruction in compressed sensing, but it is sensitive to the initial point and converges to a local optimal solution. Therefore, to overcome its shortcoming, in this paper a hybrid hard thresholding algorithm (HHT) is derived by introducing the simulated annealing algorithm (SA) into the IHT. And a series of experiments are provided on signal and image reconstruction to assess performance of the algorithm. The experiments and applications show that the proposed algorithm uses less sampling to construct the signal and image and is more stable, as compared with IHT.