The Application Of Frame Selection Technology In The Solar High-Resolution Imaging

In solar observation, getting high-resolution solar image is important for studyingthe small scale struction of the sun. But the ground-telescope can’t actualize diffractionlimted imaging owe to atmospheric turbulence. Adaptive Optics (AO) andHigh-resolution Statistical Reconstruction Method can overcome the influence ofatmospheric turbulence to obtain high resolution images. Frame seleciton is onetechnique offen performed in AO and High-resolution Statistical Reconstruction.Images that severely degraded are discarded according to some image quality criteria sothe time for image post-processing can be shorten, and the reconstruction effect can beimproved in some extent.The key point for frame selection is the image quality metric. In solar observations,rms of the granulation is off calculated to evaluation image quality. But when the regioncontains very dark and very bright features, the rms should be very high, it would ratherreflect the image content itself, but not the quality of the image. In this paper a frameselection method based on speckle interferometry (SI method) is proposed, itsadvantage lies in that it eliminates the information of the object and containsinformation only about the telescope and the turbulent atmosphere, can be moreaccurately reflect the effect of atmosphere turbulence.There is a simple introduction of High-Resolution Statistical ReconstructionMethod and lucky imaging which offen used by point object, then the image qualityevaluation function of extended objects and their characteristics. In chaper four, there isan introduction of the proposal and fundamental of the frame selection method based onspeckle interferometry (SI selection method for short). At last, the parameter of SI selection method is determined preliminary. In chaper five, the simulation results of Sselection method compared with the usually used frame selection method are presenteand the application of the SI selection method in solar high resolution observations arexplored.