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- W2076292775 abstract "We report on our progress toward a flexible image reconstruction software for optical interferometry capable of 5D imaging of stellar surfaces. 5D imaging is here defined as the capability to image directly one or several stars in three dimensions, with both the time and wavelength dependencies taken into account during the reconstruction process. Our algorithm makes use of the Healpix (Gorski et al., 2005) sphere partition scheme to tesselate the stellar surface, 3D Open Graphics Language (OpenGL) to model the spheroid geometry, and the Open Compute Language (OpenCL) framework for all other computations. We use the Monte Carlo Markov Chain software SQUEEZE to solve the image reconstruction problem on the surfaces of these stars. Finally, the Compressed Sensing and Bayesian Evidence paradigms are employed to determine the best regularization for spotted stars. Our algorithm makes use of the Healpix (reference needed) sphere partition scheme to tesselate the stellar surface, 3D Open Graphics Language (OpenGL) to model the spheroid, and the Open Compute Language (OpenCL) framework to model the Roche gravitational potential equation." @default.
- W2076292775 created "2016-06-24" @default.
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- W2076292775 date "2012-09-12" @default.
- W2076292775 modified "2023-10-14" @default.
- W2076292775 title "Toward 5D image reconstruction for optical interferometry" @default.
- W2076292775 doi "https://doi.org/10.1117/12.926274" @default.
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