An Automatic Image Reconstruction Procedure for the De-Saturation of SDO/AIA Images

Thursday, 18 December 2014
Richard A Schwartz1, Gabriele Torre2, Michele Piana2, Federico Benvenuto3 and Anna Maria Massone4, (1)Catholic University of America, Washington, DC, United States, (2)University of Genoa, Department of Mathematics, Genoa, Italy, (3)Ecole Polytechnique, Palaiseau Cedex, France, (4)CNR - SPIN, Genova, Italy
Images provided by SDO/AIA are often characterized by primary saturation and blooming that affect the core of the flaring region. We have formulated a computational method that utilizes several image processing techniques for the recovery of information in the primary saturation region, starting from the knowledge of the diffraction fringes. The method recognizes primary saturation by means of correlation, uses convolution to localize the diffraction fringes and applies Expectation Maximization against them to reconstruct the information in the saturation region.

We present an SSW implementation of this procedure characterized by full automation and discuss the results it provides while reconstructing a number of SDO/AIA images under a variety of artifacts and intensities. Issues like signal interpolation in the blooming region and the impact of emission line distribution in the AIA point spread functions are also discussed.