Occipital HW Leader Evan Fletcher did an interesting work on searching for an optimal CFA pattern among arbitrary large sized patterns in an unconstrained machine learning search. The result might surprise the companies proposing better CFA mosaics, such as Fujifilm:
"After training for ~24 hours, the learned color filter array looks quite familiar:
The network seems to have learned something very similar to a RGGB Bayer pattern, complete with 2×2 repetition and the pentile arrangement of the green pixels! This was quite surprising, especially given that there is no spatial constraint on arrangement or repetition in this network design whatsoever.
This optimization appears to have independently confirmed the venerable Bayer pattern as a good choice for a mosaic function – it was fascinating to see a familiar pattern arise from an unconstrained optimization."
"After training for ~24 hours, the learned color filter array looks quite familiar:
The network seems to have learned something very similar to a RGGB Bayer pattern, complete with 2×2 repetition and the pentile arrangement of the green pixels! This was quite surprising, especially given that there is no spatial constraint on arrangement or repetition in this network design whatsoever.
This optimization appears to have independently confirmed the venerable Bayer pattern as a good choice for a mosaic function – it was fascinating to see a familiar pattern arise from an unconstrained optimization."
Unconstrained Machine Learning Search Confirms that Bayer CFA is Optimal
Reviewed by MCH
on
December 05, 2018
Rating:
Reviewed by MCH
on
December 05, 2018
Rating:
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