Skariah, Deepak G and Arigovindan, Muthuvel (2017) Nested Conjugate Gradient Algorithm With Nested Preconditioning for Non-Linear Image Restoration. In: IEEE Transactions on Image Processing, 26 (9). pp. 4471-4482. ISSN 1057-7149
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Abstract
We develop a novel optimization algorithm, which we call nested non-linear conjugate gradient (CG) algorithm (NNCG), for image restoration based on quadratic data fitting and smooth non-quadratic regularization. The algorithm is constructed as a nesting of two conjugate gradient iterations. The outer iteration is constructed as a preconditioned non-linear CG algorithm; the preconditioning is performed by the inner CG iteration that is linear. The inner CG iteration, which performs preconditioning for outer CG iteration, itself is accelerated by an another FFT-based non-iterative preconditioner. We prove that the method converges to a stationary point for both convex and non-convex regularization functionals. We demonstrate experimentally that proposed method outperforms the well-known majorization-minimization method used for convex regularization, and a non-convex inertial-proximal method for non-convex regularization functional.
Item Type: | Journal Article |
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Publication: | IEEE Transactions on Image Processing |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Additional Information: | The copyright for this article belongs to the Institute of Electrical and Electronics Engineers Inc. |
Keywords: | conjugate gradient method; convex regularization; Image restoration; nonconvex regularization; optimization; preconditioning |
Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
Date Deposited: | 13 Jun 2022 12:03 |
Last Modified: | 13 Jun 2022 12:03 |
URI: | https://eprints.iisc.ac.in/id/eprint/73411 |
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