Print Email Facebook Twitter Semidefinite programming for model-based sensorless adaptive optics Title Semidefinite programming for model-based sensorless adaptive optics Author Antonello, J. Verhaegen, M.H.G. Fraanje, R. Van Werkhoven, T. Gerritsen, H.C. Keller, C.U. Faculty Mechanical, Maritime and Materials Engineering Department Delft Center for Systems and Control Date 2012-10-22 Abstract Wavefront sensorless adaptive optics methodologies are widely considered in scanning fluorescence microscopy where direct wavefront sensing is challenging. In these methodologies, aberration correction is performed by sequentially changing the settings of the adaptive element until a predetermined image quality metric is optimized. An efficient aberration correction can be achieved by modeling the image quality metric with a quadratic polynomial. We propose a new method to compute the parameters of the polynomial from experimental data. This method guarantees that the quadratic form in the polynomial is semidefinite, resulting in a more robust computation of the parameters with respect to existing methods. In addition, we propose an algorithm to perform aberration correction requiring a minimum of N+1 measurements, where N is the number of considered aberration modes. This algorithm is based on a closed-form expression for the exact optimization of the quadratic polynomial. Our arguments are corroborated by experimental validation in a laboratory environment. To reference this document use: http://resolver.tudelft.nl/uuid:f6ab426a-997d-44e3-90c1-27c841380ec7 DOI https://doi.org/10.1364/JOSAA.29.002428 Publisher Optical Society of America ISSN 1084-7529 Source http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-29-11-2428 Source Journal of the Optical Society of America A, 29 (11), 2012 Part of collection Institutional Repository Document type journal article Rights © 2012 Optical Society of America Files PDF Antonello_2012.pdf 635.08 KB Close viewer /islandora/object/uuid:f6ab426a-997d-44e3-90c1-27c841380ec7/datastream/OBJ/view