The Theory And Algorithms Of Adaptive Optics Image Restoration

All the optical imaging systems which work in atmospheric circumstance will face the problem of imaging through atmospheric turbulence.Before the light comes into the focus of imaging sensor, atmospheric medium may affect or disturb the ideal transmission of light,which will cause several effects, such as the aberrance of wave front of object's reflecting electromagnetic wave,the diffusion of image point intensity distribution in the focal plane,the reduce of peak value and the excursion of light beam.In the end,it will cause the blurring of image and badly impact the imaging capability of optical systems. The technology of adaptive optics is one of the most effective methods of overcoming atmospheric turbulence.But it cannot completely compensate the atmospheric turbulence,and the high frequency information of objects may be bated and reduced.So the image which has been rectified by adaptive optics should be post-processed by the technology of image restoration,and then it will be a clearer object image.This paper mainly aims at the imminent need of imaging post-process of adaptive optics groundwork telescope in our country,and uses the technology of signal process and computer software to restore high-legible image and eliminate the remain error of adaptive optics correction,so it will meet or reach the diffraction limit of imaging system.The paper mainly researches on the theory and algorithm of adaptive optics image restoration and at the same time discusses and analyzes the problems of adaptive optics wave-front reconstruction and the evaluation of image restoration quality.The main work include as follows:1.It developed a demo system of adaptive optics imaging theory.According to the theory of wave's atmospheric turbulence transmission,it analyzes the effect of turbulence on long-expose OTF and short-expose OTF.Based on the presentation of adaptive optics system's constitution and work theory,it designed a simple demo system CYAOIS of adaptive optics imaging theory based on SCIAO platform.2.It defined the synthetical evaluation index of image restoration quality.Aimed at the shortage of existing image restoration quality evaluation methods which cannot consider the fake image,it defined a synthetical evaluation index of image restoration quality based on subarea local variance change statistic according to the human eyes vision characteristic.The experiment proved that this index is an effective and objective index to evaluate non-reference image restoration quality.3.The wave-front reconstruction of adaptive optics image based on generalized ridge estimation.In the view of adaptive optics image post-processed restoration,real time and fast computation are not the basic request of wave-front reconstruction,but the high-precision.On the consideration of sacrifice time for precision,it brought the idea of generalized ridge estimation(GRE) and iterative solution into wave-front reconstruction,and presented a wave-front reconstruction algorithm of generalized ridge estimation's Zernike mode based on image restoration.The experiment proved that the algorithm which restored PSF had performed well in image restoration.4.PSF estimation of degraded image based on non-sample wavelet transformation.In the problems of image restoration,PSF estimation is the main part of the algorithm.It brought non-sample wavelet transformation into the PSF estimation of blurred image.Based on the Fried parameter model and the relationship between module max value of wavelet transformation and the variance of Gauss point spread function in different scale,it presented a PSF estimation algorithm based on the non-sample wavelet transformation.The experiment proved that the algorithm had well PSF estimation precision in adaptive optics image without pre-wave survey data.5.Adaptive optics image restoration based on ENAS-RIF algorithm.Aimed at the shortage of ENAS-RIF algorithm it brought image pre-process of Curvelet denoise,credible support region, object construction restriction item and enhanced cost function into NAS-RIF algorithm And it presented ENAS-RIF algorithm based on credible support region and enhanced cost function.The experiment of adaptive optics image restoration proved that the convergence speed of ENAS-RIF algorithm was faster than NAS-RIF algorithm and it did well in image restoration.6.Adaptive optics image restoration based on IRL-IBD algorithm.On the basis of non-symmetry IBD algorithm,it improved the reliability of algorithm by introducing the bandwidth finite restriction into PSF frequency domain and the convergence speed of algorithm by introducing dynamic support region into PSF estimation,and it presented multi-restriction non-symmetry IRL-IBD algorithm into adaptive optics image restoration.The experiment proved that reformative IRL-IBD algorithm was better than IBD algorithm7.Eliminating ill frame of image sequence based on variance statistic.In the restoration of multi-frame image,some observation images with bad quality cannot contribute to the image restoration,but may badly affect the quality of restored images.It used the characteristics that additive noises may increase the variance of blurred image and PSF blurring may decrease the variance of blurred image, and considering the idea of outliers detection in photogrammetry it designed an automatic detection scheme of ill frame based on image variance statistic.The experiment proved that the image restoration was better after the detection of ill frame.8.The MF-MAPJD high-resolution restoration of multi-frame adaptive optics image based on MAP.In the frame of Bayesian,according to the characteristic of adaptive optics image,it redefined the mixed noises model and the priori model of object construction,and then added PSF restriction item into cost function,and designed a simple self-poise scheme of regularization restriction.And it presented a multi-frame combination deconvolution algorithm MF-MAPJD for AO image.The experiment proved that the new algorithm considered both the point spread function and object,and made the best of all the priori restriction information in the image sequence,and it proved that the quality of image restoration was better.9.Adaptive denoise of image based on the second generation Curvelet transformation.According to the trait that Curvelet transformation is sparser than image signal,and combined with Bayesian Shrink theory,it presented an improved adaptive image denoise algorithm of Curvelet domain.The experiment proved that it was better to denoise than wavelet algorithm.10.Adaptive optics image restoration based on second generation Curvelet transformation It brought multi-scale and multi-direction idea into image process,and considered the idea of image Fourier-Wavelet hybrid domain regularization deconvolution,and then it proposed the image Fourier-Curvelet hybrid domain regularization deconvolution(ForCuRD) based on second generation Curvelet transformation.ForCuRD algorithm used both the Fourier domain constriction and Curvelet domain constriction,and overcame the shortage of single transformation domain constriction,and lend a new way for the research of adaptive optics image restoration.