AIA Images Enhancement Method Based on Blind Deconvolution

There are various physical activities in the solar images, such as different scales, brightness and structure. Due to the high dynamic activity of the solar corona and sensor equipment, the image quality of solar imaging is poor. According to the characteristics of large dynamic range, large noise and relatively fuzzy structure of different waveband data structures captured by the atmospheric imaging asset (AIA) of the solar dynamic Observatory (SDO), an effective SDO/AIA image enhancement method based on blind deconvolution is proposed in this paper. Firstly, the SDO/AIA image is denoised and the dynamic range is reduced. Based on the distribution assumption of image power spectrum, the point spread function (PSF) is estimated from the original image. Then, phase retrieval algorithm is used to recover the phase of PSF, and then deconvolute the high-quality target image; finally, the enhancement results are analyzed quantitatively and qualitatively through slice analysis, power spectrum analysis and PSF analysis. The experimental results show that, compared with the existing image enhancement methods, the proposed method can effectively enhance the detail structure of the solar corona image, and restore the structure that cannot be identified due to the blur of the original image.