Thank you for your response,
i still have one more question. I found my webcam do some strange scale
work. For example the image detalisation of 640x480 is equal to the
image with 400x300 resolution. If i grab 800x600 and downscale it to
640x480 i get better result.
Do you know how scale logic is done on webcams? Or probably where i can
read about it?
Am 29.08.2011 09:58, schrieb jean-philippe francois:
2011/8/29 Alexey Fisher <bug-tr...@fisher-privat.net
<mailto:bug-tr...@fisher-privat.net>>
Hallo all,
i know some people here was working with bayer raw data. I just
discovered this word for me, so i need some help to understand it
correctly.
Normal bayer based image sensor have separate pixel for each color.
Usually it made in 4 pixel squares, 1 - blue, 1 - red, 2 - green.
There are different ways to precess this data but most easiest one
will get one image pixel out of 4 physical pixels.
This also mean, if my (for example) webcam has physical sensor size
of 2MP, the real, not interpolated image data is MP*0.25.
1600x1200 (claimed resolution(2MP)) /2 = 800x600 (real/perfect image
resolution(0,5MP))
Is this correct?
I don't think the word 'real' is useful here.
If you treat pixel data as black and white data,
you can see pixel size details. Of course this black
and white image is polluted by the fact that for a given
visible light quantity, a green pixel won't give you the
same value as a blue pixel, and the resulting image
will look like a mozaic.
If you take 4 pixels to make a half-sized image, you will
miss some details. Not doing interpolation does not mean
your image is more perfect or more real. It is just a suboptimal
usage of data at your disposal.
Let's suppose you could have three monochrome sensor with
the same resolution as your webcam each taking the exact
same image.
From this image, you can construct a subsampled image
at half the resolution.
With bayer data, smaller details than in the subsampled
'perfect' image are available, yet you can only have and
approximation of the full resolution image.
The better your interpolation, the closer you are from
the 'perfect' image, for some definition of perfect.
Regards,
Alexey.
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