Study On The Algorithms Of Adaptive Optical Images Restoration

Obtaining the high-legible images is of great importance in the area of astronomy, remote sensing and medical imaging. The atmosphere is an unstable stochastic medium, which will badly limit the resolution of the optical system in ground-to-space observation imaging and space-to-ground remote sensing high resolution imaging process. In the end, it will affect the imaging capability of optical system and cause the blurring of the images. 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 is still restrained and attenuated. 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 main research of the paper is concerning about the theory and algorithm of adaptive optics image restoration. The main work includes as follows:1. The detailed introduction of the adaptive optics technologies. This part includes the concept and the characteristics of the atmospheric turbulence, the principle and formation of the adaptive optics technology, the beginning and development of the adaptive optics technology, the main adaptive optical system at present, the limitations of the adaptive optics technology.2. The summary of the important algorithms of the adaptive optics image restoration. It analyzes and then presents the imaging model and the noisy characteristics of the adaptive optics images. It classifies the commonly used algorithms, introduces the principles and the main calculating formulations and points the advantages and disadvantages of each algorithm, introduces some evaluation index of image restoration quality.3. The improvement of the Wiener filter and the realization of the regularized Wiener filter algorithm based on the LPA-ICI. Aiming at the shortcomings of the Wiener filter, and combined with the denoising algorithm of anisotropic LPA-ICI, it presents a regularized Wiener filter algorithm based on the LPA-ICI. It firstly introduces the basic principles and the developing process of the anisotropic LPA-ICI, then realizes a new recursive LPA-ICI algorithm for image denoising, and it separately does some experiments with the image polluted by Gaussian noise or Poisson noise, which approves the advantages of the algorithm. In the end, it introduces the regularized Wiener filter algorithm based on the LPA-ICI, including the principle, calculating formulations and calculating processes of the algorithm, moreover it does restoration experiments of degraded images with different noises, which testifies the advantage of the algorithm.4. The proposition and realization of a multi-frame IBD algorithm based on Dual Tree Complex Wavelet Transform (DTCWT). It firstly introduces the developing process, basic principles and advantages of the DTCWT in detail. Then it realizes the adaptive denoising algorithm based on DTCWT, presents the basic principles and main processes. Then it approves the superiority of DTCWT. In the end, aiming at the shortcomings of the IBD algorithm and algorithm of Zhulina, it proposes the multi-frame IBD based on the DTCWT, introduces the principles, main calculating formulations and the calculating processes of the algorithm. In the end it approves the advantage of the algorithm through experiments with the simulated data and true data.5. The proposition and realization of blind restoration algorithm based on projection gradient. Aiming at the shortcomings of the cost functions of the least squares method and Katkovnik's algorithm, it proposes a new cost function, then minimizes it by projection gradient algorithm, and combines the restricted conditions to obtain the final iterative formulas, It realizes the multi-frame blind image reconstruction based on projection gradient. The principle of the algorithm is simple and the algorithm is easily realized. The experiments with the simulated data and true data demonstrate the algorithm works efficiently. For images of different noise grades and PSF types, it can clearly restore detail features of images.