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A practical approach on non-regular sampling and universal demosaicing of raw image sensor data
  DOI :  10.2352/issn.2694-118X.2020.LIM-17  Published OnlineSeptember 2020
Abstract

Non-regular sampling is a well-known method to avoid aliasing in digital images. However, the vast majority of single sensor cameras use regular organized color filter arrays (CFAs), that require an optical-lowpass filter (OLPF) and sophisticated demosaicing algorithms to suppress sampling errors. In this paper a variety of non-regular sampling patterns are evaluated, and a new universal demosaicing algorithm based on the frequency selective reconstruction is presented. By simulating such sensors it is shown that images acquired with non-regular CFAs and no OLPF can lead to a similar image quality compared to their filtered and regular sampled counterparts. The MATLAB source code and results are available at: http://github. com/PhilippBackes/dFSR

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Philipp Backes, Jan Fröhlich, "A practical approach on non-regular sampling and universal demosaicing of raw image sensor datain Proc. IS&T London Imaging Meeting 2020: Future Colour Imaging,  2020,  pp 91 - 95,  https://doi.org/10.2352/issn.2694-118X.2020.LIM-17

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Copyright © Society for Imaging Science and Technology 2020
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London Imaging Meeting
2694-118X
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