Optimization and Application of Lucy-Richardson Filter on Optical Remote Sensing Image Restoration

In complex space environment, remote sensing imaging process might be affected by different kinds factors. Lucy-Richardson (L-R) filter method is an extensive used method in image reconstruction field. In order to decrease the calculation time and promote the quality of image, a optimal semi-blind remote sensing data reconstruction algorithm based on improved L-R filter is presented. Firstly, self-correlation function is innovated to calculate the point spread function (PSF). To suppress the superposition of noise in L-R iterative process, both full-reference and no-reference evaluation parameters are applied in iteration termination conditions. Finally, Gaussian filter is adopted to filtrate low-pass signal when the noise is constantly amplified. Experiments and simulation results explanation that the improved Lucy-Richardson filter algorithm could gain relatively satisfactory reconstruction effects. And the proposed processing method could be used for the restoring and reconstruction of those remote sensing data degraded by rectilinear motion and random noise interference.