Study On Restoration Of Adaptive Optics Images Based On Frozen Flow Hypothesis

The images of space objects obtained through large ground-based optical telescopes are usually severely blurred by atmospheric turbulence.The wavefront distortion caused by atmospheric turbulence can be compensated by adaptive optics(AO)through real-time measurement and correction.However,the compensation is partial because of the error of the wavefront measurement and correction and the delay of the real-time-control system,and etc.Therefore,AO images must be restored by post-processing methods for further utilization.Multi-frame blind deconvolution(MFBD)is a commonly used method for AO image restoration.The object can be recovered from multi-frame short exposure degraded images of the object using optimization methods based on the Bayesian framework.However,similar to AO’s compensation,high-quality restorations can be obtained only under conditions of weak and moderate turbulence.In order to improve the quality of AO image restoration under strong turbulent conditions,this thesis combines the traditional MFBD algorithm with the wavefront reconstruction technique,where the wavefront reconstruction is based on the frozen flow hypothesis(FFH).First,the high-resolution reconstructed wavefront is used to provide high-quality initial estimates for the point spread functions and strong physical constraints for the restoration process.Secondly,a feasible technical approach for strong turbulence imaging is explored by joint restoration of images observed through different imaging diameters.The main innovations and research results are as follows:1.Based on the FFH,the wavefront measurements of the Shack-Hartmann wavefront sensor(SH-WFS)are used to reconstruct high-resolution wavefront phases in the pupil of the telescope.Simulated results show that the proposed high-resolution wavefront reconstruction method based on maximum a posterior framework has higher wavefront reconstruction accuracy than the "two-step" method,and is robust to wind speed estimation error and wavefront measurements noise.2.Based on the high-resolution wavefront reconstruction method,a new AO image restoration algorithm based on wavefront sensing is proposed.It uses the reconstructed high-resolution wavefront to provide high-precision initial estimation of the wavefront for the improved MFBD,and uses the gradient measurements and the FFH to provide strong physical constrains.According to the fact that the 2D dual-tree complex wavelet transform has the capability of feature extraction and good directional selectivity,a regularization method based on the dual-tree complex wavelet transform is proposed.Simulated results show that the proposed algorithm can significantly improve the quality of image restoration and suppress noise and preserve the edge of the restored image.3.In view of the need for high-resolution imaging under strong turbulence conditions,a high-resolution phase retrieval method using the Imaging Shack-Hartmann structure is proposed.Based on the characteristics of both aperture segmentation and image acquisition,high-resolution wavefront estimation is obtained using the modified phase retrieval method,where the FFH is used to ensure the continuous of the estimated wavefront.Simulated experiments show that the proposed method can achieve higher accuracy than the slope-based high-resolution wavefront reconstruction method.4.A new high-performance space object imaging method based on multi-channel joint image restoration is proposed by incorporating the observations of the imaging Shack-Hartmann with those of the conventional full-aperture imaging channel.High-resolution image restoration of the space object is obtained by cascaded MFBD algorithm using all image data of the two channels,where the wavefront phases estimated using the imaging Shack-Hartmann are used as the initial estimates for the joint restoration.Simulated results show that the proposed multi-channel joint image restoration algorithm can achieve better image restoration quality than single-channel image restoration.