Bobby Hunt (Integrity Applications Inc.), Keith Knox (Air Force Research Laboratory)
Keywords: image restoration, deconvolution, compressive sensing
Abstract:
Multi-Frame Blind Deconvolution (MFBD) has been successful in the employment of Zernike polynomial representations for the phase errors introduced by atmospheric turbulence. In this presentation we draw on the field of Compressive Sensing and demonstrate the use of sparse representations of turbulence. We train a dictionary on turbulence point-spread-functions (PSFs), and demonstrate the effectiveness of sparsity to represent turbulence. We then present MFBD processing using the sparse turbulence representation, replacing the role of the Zernike polynomials in the MFBD process. Results and comparisons are presented.
Date of Conference: September 9-12, 2014
Track: Adaptive Optics & Imaging