Abstract:

Aiming at the shortcomings that iterative hard thresholding（IHT）reconstruction algorithm of compressed sensing theory requires the sparsity of original signal is known, a variable step size sparsity adaptive iterative hard thresholding（VSSSAIHT）algorithm was proposed. When the sparsity of original signal is unknown, the proposed algorithm according to the differences between adjacent residuals chooses appropriate step size to increase the number of support set of the reconstructed signal, approximate the sparsity of original signal gradually and restore signals by gradual iterations. Simulation results show that the VSSSAIHT algorithm, compared with the IHT algorithm, improves the quality of the reconstructed image, and reduces running time.

Key words: compressed sensing；iterative hard thresholding；image reconstruction；variable step size；sparsity adaptive