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Multiresolution-based weighted regularization for denoised image interpolation from scattered samples with application to confocal microscopy

Francis, Bibin and Mathew, Manoj and Arigovindan, Muthuvel (2018) Multiresolution-based weighted regularization for denoised image interpolation from scattered samples with application to confocal microscopy. In: JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 35 (10). pp. 1749-1759.

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Official URL: http://dx.doi.org/10.1364/JOSAA.35.001749

Abstract

The problem of reconstructing an image from nonuniformly spaced, spatial point measurements is frequently encountered in bioimaging and other scientific disciplines. The most successful class of methods in handling this problem uses the regularization approach involving the minimization of a derivative-based roughness functional. It has been well demonstrated, in the presence of noise, that nonquadratic roughness functionals such as l(1), measure yield better performance compared to the quadratic ones in inverse problems in general and in deconvolution in particular. However, for the present problem, all well-evaluated methods use quadratic roughness measures; indeed, l(1) performs worse than the quadratic roughness when the sampling density is low. This is due to the fact that the mutual incoherence between the measurement operator (dirac-delta) and the regularization operator (derivative) is low in the present problem. Here we develop a new multiresolution-based roughness functional that performs better than l(1) and quadratic functionals under a wide range of sampling densities. We also propose an efficient iterative method for minimizing the resulting cost function. We demonstrate the superiority of the proposed regularization functional in the context of reconstructing full images from nonuniformly undersampled data obtained from a confocal microscope. (C) 2018 Optical Society of America

Item Type: Journal Article
Additional Information: Copy right for this article belong to OPTICAL SOC AMER
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Depositing User: Id for Latest eprints
Date Deposited: 16 Oct 2018 14:23
Last Modified: 16 Oct 2018 14:23
URI: http://eprints.iisc.ac.in/id/eprint/60884

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