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
Philipp Backes, Jan Fröhlich, "A practical approach on non-regular sampling and universal demosaicing of raw image sensor data" in 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