Wavefront coded image restoration algorithm based on compressed sensing for off-axis mirror system

By combining optical systems and image processing, wavefront coding can greatly expand the depth of focus and depth of field of optical systems. It has been widely used in iris detection, high-power microscopic objective lens, infrared optical system athermalized, and so on. At present, the image restoration algorithms commonly used in wavefront coding are based on deconvolution, Wiener filtering, and so on. Although these algorithms can achieve an excellent image restoration effect, they will also bring boundary ringing effects and artifacts to the image. When the image is disturbed by strong noise, the restoration effect will also be seriously affected. To solve these problems, a wavefront coded image restoration algorithm based on compressed sensing is proposed in this paper. The strong data reconstruction ability of the compressed sensing restoration algorithm is used to restore the encoded image obtained by the wavefront coding system. This method can effectively suppress noise and reconstruct the image without artifact and boundary ringing effect. Through the comparison of simulation results, the effectiveness of the proposed method is verified.