High frequency noise constraint in deconvolution from wavefront sensing

This paper concerns solving deconvolution problem by constrain the noise in the degraded images in order to regularize the ill-posed characteristics. Adding constraint on degraded images during the deconvolution process, images of indoor point sources with aberration are restored. The results show that the method can constrain the noise in the high frequencies effectively and the restored images can reach the resolution of diffraction limit. Compared with the images restored by Wiener inverse filter, the images restored by noise constrained regularization have better vision quality,higher Strehl ratio and signal noise ratio.