De-Bayering Algorithms
Posted: Sat Sep 22, 2012 7:48 am
Hello,
for everyone interested in the process of de-bayering,
I've found an interesting paper that is easy to understand:
http://www.stark-labs.com/craig/articles/assets/Debayering_API.pdf
Thought the paper mentions, the best method – Variable Number of Gradients –
is not suitable for realtime, there are actually realtime-implementations of VNG out there.
Also found a test for different approaches:
http://www.linuxphoto.org/html/test_demosaicing.html
And here I found something for those who are scientifically interested in the topic:
http://scien.stanford.edu/pages/labsite/1999/psych221/projects/99/tingchen/main.htm
I would be very curious which algorithm BMCC / Resolve is using.
(Hope they are developed by Teranex' experts to guarantee maximum quality! )
Best regards,
Bernhard
for everyone interested in the process of de-bayering,
I've found an interesting paper that is easy to understand:
http://www.stark-labs.com/craig/articles/assets/Debayering_API.pdf
Thought the paper mentions, the best method – Variable Number of Gradients –
is not suitable for realtime, there are actually realtime-implementations of VNG out there.
Also found a test for different approaches:
http://www.linuxphoto.org/html/test_demosaicing.html
And here I found something for those who are scientifically interested in the topic:
http://scien.stanford.edu/pages/labsite/1999/psych221/projects/99/tingchen/main.htm
I would be very curious which algorithm BMCC / Resolve is using.
(Hope they are developed by Teranex' experts to guarantee maximum quality! )
Best regards,
Bernhard