Independent component analysis approach to image sharpening in the presence of atmospheric turbulence

Abstract

An independent component analysis (ICA) approach to image sharpening is presented for incoherent imaging through weak atmospheric turbulence. Taking account of the turbulence model a novel data representation scheme is used for the ICA algorithm wherein each selected image frame is treated as a sensor. The proposed concept enables one diffraction limited object image and several images that correspond to atmospheric turbulence patterns to be extracted as separate physical sources. By using an image sharpening metric based on the Laplacian operator, it is shown that the ICA algorithm when applied to experimental data with known ground truth gives better results than obtained by the frame averaging method.