Research and Improvement of Remote Sensing Image Restoration Algorithm Based on Wiener Filter

On the condition of spatial imaging, remote-sensing images are always blurred by many elements. Wiener filter method is broadly used in semi-blind image restoration field. To avoid complex operations of power spectrum ratio in traditional Wiener filter, a new semi-blind remote sensing image recovery method on the basis of improved Wiener filter and comprehensive evaluation factor was presented. The method adopts improved Wiener filter to restore the blurred remote sensing data. And the degraded function factor is appraised via linear motion model. The power spectrum specific value of acquired remote sensing image is evaluated through multiple iterative calculation. Iterative stopping condition is stipulated by an integrated evaluation parameter, which is comprised of three no-reference quality parameters, GMG, IE and CF. Simulations and experiments indicate that the improved Wiener filter method acquires relatively approving restoration results and time overhead. And the proposed algorithm could be applied in restoring the remote sensing images blurred by linear motions and Gaussian noise.