Now that we have high resolution, why isn't "binning" a standard option?

RichA wrote:

The combining of pixels into superpixels prior to digitization. 4
pixels of 7um become one of 14um. Low light shooting becomes much
easier as effective ISO is raised. Not every situation calls for 12
megapixels of resolution, but often situations call for low light
capability.

What's wrong with binning in PP? I don't see a real need for in camera.

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The combining of pixels into superpixels prior to digitization. 4
pixels of 7um become one of 14um. Low light shooting becomes much
easier as effective ISO is raised. Not every situation calls for 12
megapixels of resolution, but often situations call for low light
capability.

Ï "RichA" Ýãñáøå óôï ìÞíõìá
ups.com...

The combining of pixels into superpixels prior to digitization. 4
pixels of 7um become one of 14um. Low light shooting becomes much
easier as effective ISO is raised. Not every situation calls for 12
megapixels of resolution, but often situations call for low light
capability.


Excellent question and i presume quite easy to implement at the sensor
level.

In article . com, RichA
writes
The combining of pixels into superpixels prior to digitization. 4
pixels of 7um become one of 14um. Low light shooting becomes much
easier as effective ISO is raised. Not every situation calls for 12
megapixels of resolution, but often situations call for low light
capability.


At the sensor level those 4 colour 7um pixels become one monochrome 14um
pixel - and your image reduces to 3Mp.

To do binning on a conventional Bayer array while retaining colour
information means combining non-adjacent pixels. That means even more
complex circuitry and tracking in an already dense pixel. That, in
turn, means the signal losses may swamp any noise benefits.

For example, any 4x4 array on a standard Bayer sensor has 4 red, 4 blue
and 8 green pixels. Each colour pixel has pixels of the other colours
between them, so adjacent pixels cannot be binned. However non-adjacent
pixels could be combined to give 1 red & blue and 2 green superpixels in
a 2x2 array, with each superpixel spanning a 3x3 area of the originals.
So, if your original pixels are 7um then the superpixels are actually on
a 21um in size, but on a 14um pitch. ie. the superpixels physically
overlap. That may not be a bad thing, since spatial coherence between
pixels is Foveon's main feature, but the resolution would be less than a
conventional 3Mp sensor.
--
Kennedy
Yes, Socrates himself is particularly missed;
A lovely little thinker, but a bugger when he's ****ed.
Python Philosophers (replace 'nospam' with 'kennedym' when replying)

Kennedy McEwen wrote:

RichA writes

The combining of pixels into superpixels prior to digitization. 4
pixels of 7um become one of 14um. Low light shooting becomes much
easier as effective ISO is raised. Not every situation calls for 12
megapixels of resolution, but often situations call for low light
capability.

At the sensor level those 4 colour 7um pixels become one monochrome 14um
pixel - and your image reduces to 3Mp.

To do binning on a conventional Bayer array while retaining colour
information means combining non-adjacent pixels. That means even more
complex circuitry and tracking in an already dense pixel. That, in
turn, means the signal losses may swamp any noise benefits.

For example, any 4x4 array on a standard Bayer sensor has 4 red, 4 blue
and 8 green pixels. Each colour pixel has pixels of the other colours
between them, so adjacent pixels cannot be binned. However non-adjacent
pixels could be combined to give 1 red & blue and 2 green superpixels in
a 2x2 array, with each superpixel spanning a 3x3 area of the originals.
So, if your original pixels are 7um then the superpixels are actually on
a 21um in size, but on a 14um pitch. ie. the superpixels physically
overlap. That may not be a bad thing, since spatial coherence between
pixels is Foveon's main feature, but the resolution would be less than a
conventional 3Mp sensor.

Is binning any better that downsampling?

In article , Paul Furman
writes

Is binning any better that downsampling?

In principle, yes, since you only have one read operation and therefore
one read noise contribution, with sqrt(n) photon signal to noise. The
problem comes with whether that sqrt(n) can be achieved in practice
without any signal losses or additional noise. Downsampling, in
contrast, has n read noise contributions.
--
Kennedy
Yes, Socrates himself is particularly missed;
A lovely little thinker, but a bugger when he's ****ed.
Python Philosophers (replace 'nospam' with 'kennedym' when replying)

At the sensor level those 4 colour 7um pixels become one monochrome 14um
pixel - and your image reduces to 3Mp.

What would the sensitivity of that monochrome pixel be though? Would
it be the mean average of the sensitivities of the four pixels? That's
what I'm assuming. I'm just wondering how the difference between the
density of the green pixel filtration (relatively minor) and the blue
pixel filtration (around 3 stops) would change how the binning
operates. You seem to know about these things.

Will