In
unbinned imaging, the signal from each pixel is associated with a given
amount of read noise. For instance, 4 pixels would be associated
with 4 separate read noise
events, since each pixel is read individually. Binning
is a procedure in which several pixels are grouped into a function
unit, which has the effect of reducing the impact of read
noise on the signal to noise ratio (SNR). In
2x2 binning, for example, an array of 4 pixels forms a functional
"superpixel," accumulating the same signal as 4 individual pixels, but
associated with only 1 read noise event (since the entire superpixel is
read out as a unit). However, the larger functional pixel size
with binning results in lower resolution of the final image.
Below I express these
concepts mathematically and derive some illustrative graphs of the
effects of binning at a dark site and at a light polluted site.
If you are not interested in the math, just skip to the summary
discussed in point #2 below. Another excellent site that explains
these
concepts may be found here.
1.
From
equation 6 on my subexposure
duration page, note that the signal to noise ratio per pixel in the
total (cumulative) exposure is:
SNR
(Tot) = sqrt[K*tsub]*(Obj) /
sqrt[(Sky+Obj)*tsub +
R2],
where K is the
total (cumulative) exposure time, tsub is the subexposure duration,
Obj
is the object flux in e/pixel/min, Sky is the sky flux in
e/pixel/minute, and R is the read noise in e RMS.
2. Let's
derive
the equation for the SNR (binned 2x2)
contributed by the signal from a binned 4 pixel unit (the
"superpixel"), over a total (cumulative) exposure K. It would
simply be:
SNR
(binned 2x2, i.e., 4 pixels) = sqrt[K*tsub]*4*(Obj) /
sqrt[4*[(Sky+Obj)*tsub]+
R2]
Compared to
just one pixel, the
signal is obviously 4 fold greater since we are now collecting light
over an area of 4 pixels. But notice something important about
the noise. The noise increases, but this is due only to the
increased contribution of photon
noise, not read noise (note the yellow parentheses). This
is the power of binning, since the read noise contribution does not
increase, even though 4 pixels are being read out. They are
viewed as a unit. More on this topic can be found near the end of
the page on this informative
website.
3. Now let's
derive the comparable equation for the SNR of 4
pixels read out individually (i.e., unbinned):
SNR (4 pixels, but unbinned) =
sqrt[K*tsub]*4*(Obj) /
sqrt[4*[(Sky+Obj)*tsub+ R2]]
Notice that it's
the
same signal (i.e., 4 fold greater than one pixel),
but look at what's happened to the noise. Since each pixel is being read out, the
entire noise component (photon plus read noise) is increased 4 fold
(note the yellow parentheses).
4. Using these two
equations and applying some arbitrary (but
reasonable)
initial values for the variables at a dark site versus light polluted
site yields the following graphs:
Graph of binning
at a dark site.
Conditions are stated in the figure legend and include a total
(cumulative) exposure time of 6 hours for both curves. Dark site
in this example is defined as sky flux = 5 e/pixel/minute. The
exact number is not as important as the principle illustrated by the
shape of the curves.
Graph of binning
at a
light polluted site. As
above, conditions are stated in
the figure legend and include a total (cumulative) exposure time of 6
hours for both curves. Light
polluted site in this example
is defined as sky flux = 100 e/pixel/minute. The exact number is not as
important as the principle illustrated by the shape of the curves.
1.
Binning is
mainly useful
for reducing the subexposure
duration, but this is
relevant only if you
feel that the calculated subexposure duration (unbinned) is
unacceptably long.
This
might occur, for
instance, when imaging at a dark site, using a high read noise camera,
a narrowband filter with a tight
bandpass, and/or a
high f
ratio.
However, if the noise contribution
from sky glow is already dominant in your subs, reducing the effective
read noise contribution with 2x2 binning will have very
little effect. For instance, if you have a low read noise camera
and are taking a luminance image at a light polluted site, your
calculated subexposures will typically be quite short, and binning
would provide little advantage but will compromise resolution (image
scale at 2x2 binning is twice that of unbinned, etc.). Also, note
that binning will not appreciably improve the final signal to noise ratio of the
cumulative exposure, assuming that your subs are photon limited.
For photon limited subs, an upper limit on the S/N ratio is imposed by
the equation shown in line 8 of my subexposure duration page.
The downside of binning is a reduction in resolution if your unbinned
images are already undersampled (or borderline undersampled). So
only use binning if you are
very well sampled to start with, and if you feel the need to shorten
your subexposure duration due to the reasons mentioned above. On
the other hand, if your calculated subexposure durations (unbinned) are
within a perfectly acceptable range (however you wish to define that,
based upon your mount, accuracy of polar alignment, and patience), then
you do not need to bin.
2.
The other use of
binning is to achieve an image scale that is
more realistic for the seeing conditions. For instance, if your
image scale unbinned is 0.3 arcsec/pixel, but if your seeing is at best
2.0 arcseconds, then you are wasting effort by imaging unbinned (i.e.,
you are oversampled, resulting in decreased sensitivity without a gain
in resolution, and at the same time placing more demands on your mount
and guider). This is because an unbinned image scale of 0.3
arcsec/pixel represents a sampling rate appropriate for seeing
conditions of roughly 0.3 x 3 (Nyquist), or about 0.9 arcseconds.
You can't resolve 0.9 arcseconds if your seeing is 2.0
arcseconds. Binning can be very helpful in this situation.
If you bin such a system 2x2, the image scale becomes 0.3 x 2, or 0.6
arcsec/pixel. This is appropriate for a seeing of roughly 0.6 x 3
(Nyquist), or about 1.8 arcseconds, which is now well matched for your
seeing of 2.0 arcseconds. Your images will not suffer any loss of
resolution compared to the 0.3 arcsec/pixel image scale (because seeing
is the limiting factor), but your system will be more manageable from
the standpoint of autoguiding and file size.
Steve
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