Camera Properties and ISO
A lot has been said about which ISO should be used for imaging. Part of the problem
with the term ISO is that it came from the days of film. Here ISO really meant the
number of photons detected by the silver grains, so using different ISO film actually
changed the Quantum Efficiency. The same, however, is not true of DSLR’s. Here ISO
does not mean the Quantum Efficiency of the image sensor. Where the ISO is applied is
much further down the road than where the photoelectrons are first generated.
Imagine a constant stream of photons is incident on a pixel. In a set amount of time, you
will record a set number of photons, which will in turn produce a set number of electrons.
The ISO is applied as part of the measurement routine, and as such can have absolutely
no influence on how efficiently the pixel generates charge. Changing the ISO only and
leaving everything else the same, and then recording another image of the same duration
with the same arrival rate, will produce the same number of electrons in that pixel. Whilst
ISO has no effect on QE, it can have other effects, and so a small experiment in to the
variation of read noise, Gain (KADC) and full well with ISO was performed.
Performing the experiment is quick and painless. A canon 300D DSLR was setup with no
lens in place. The reason for this is too ‘blur’ any non uniformity in illumination. One
needs to capture 2 flat field images and 2 bias frames at each ISO. I pointed my un-lensed
camera at a nearby, roughly evenly illuminated wall. A quick stretch of a trial shot
showed this was sufficient. Aim for a 50% exposure. In fact because we are taking two
images it is not necessary to have a perfect flat field or a high signal flat, but it would
help from an SNR point of view. Take two flats and two bias frames at each ISO in RAW
mode. To estimate full well, note that as we increase exposure the average value of our
flat field increases, as does the standard deviation. A point will come when either the
average value stops increasing, indicating that the pixel is saturated, or when there is a
sudden drop in standard deviation, that occurs when the ADC is saturated. We want to
know the point at which either of these situations first occurs. When you notice that the
average value is not increasing, or that the standard deviation has suddenly dropped, note
down this number. This will be the onset of full well.
Convert the RAW files to either TIFF or FITS. Choose a 100x100 crop, say, of an area
with an even illumination. Crop all images to this selection box. Open up both flat fields,
which are now 100x100 in size. Find the average of each of these boxes and note them
down. Now subtract one image from the other. Add around 2000 or 3000 DN or ADU to
avoid having zeroes. In other words don’t clip the histogram. From the differenced
image, find the standard deviation, and square it. Note this down. Now open two bias
frames, crop these to the same 100x100 box. Again, find the average of each bias frame,
and note it down. Now difference the bias frames, using an offset of say 500DN. Record
the standard deviation, then square it, and record this number too.
The gain is used to convert from DN units to the absolute units of electrons. The equation
to use is:
Gain= (F1+F2)-(B1+B2)/(2F1-F2 - 2B1-B2)
Where F1, B1 etc are the average value of the flat field and bias 100x100 box. 2F1-F2 is
the square of the standard deviation of the differenced flat field. Similar for the bias
frames.
Now that the gain is worked out everything is easy. You should have noted down the
standard deviation of the differenced bias frames. This is the DN read noise. Multiply by
the gain to convert to electrons. You need to divide both the DN read noise and the
subsequent electron read noise by a factor of 2. This arises from subtracting two images.
This is your read noise.
RN(e-)=Gain*B1-B2/2
Next multiply the value noted down for the onset of full well, and multiply this by the
gain. This is your well capacity in electrons.
Full Well(e-)= Full Well (DN)*Gain
To calculate the dynamic range you need to divide the well capacity by the read noise.
DR=Full Well (e-)/Read Noise (e-).
Results for Canon 300D
The results for the canon 300D are shown below:
ISO
Gain (e-/DN)
Read Noise(e-)
Full Well (e-)
100
200
400
800
1600
2.3
1.3
0.48
0.3
0.12
21
16
11.1
11.7
9.4
150,000
84,000
31,000
19,300
7,800
Dynamic
Range
7100, 77dB
5200, 74.3dB
2800, 69dB
1700, 64.6dB
900, 59.1dB
Read Noise vs ISO
25
Read Noise (e-)
20
15
10
5
0
0
200
400
600
800
1000
1200
1400
1600
1800
1600
1800
ISO
Full Well (e-) vs ISO
160000
140000
Full Well (e-)
120000
100000
80000
60000
40000
20000
0
0
200
400
600
800
1000
ISO
1200
1400
Dynamic Range vs ISO
8000
7000
6000
Dynamic Range
5000
4000
3000
2000
1000
0
0
200
400
600
800
1000
1200
1400
1600
1800
ISO
Interpretation of Results
Several trends are immediately seen. The first is the decreasing full well as ISO is
increased. This is explained by the decreasing gain. If the gain, that is, e-/DN is lowered,
then the reciprocal of that, ie DN/e- is increased. Increasing the DN/e- means that every
electron of charge is digitised to a higher number. Before long the ADC saturates before
pixel full well is reached. Hence the full well falls with gain, and hence ISO. The reason
for the gain decreasing, is so that a short exposure, or an exposure containing low signal
is digitised to a high DN count, so that the image is easy to see. This is the purpose of the
ISO. It enables an other dim image to be viewed easier. The image is brighter but
contains no more signal than another exposure at a lower ISO with the same integration
time. Also evident is the falling read noise with higher ISO. This can be explained if the
ISO is changed by altering the sensitivity of the sense node. There is a noise associated
with the sense node, called Reset Noise. After a pixel of charge has been dumped on to
this node and its charge converted to a voltage, it is reset to a reference voltage level.
This process is not done perfectly and a noise associated with this resetting is introduced.
Reset Noise is eliminated in CCD sensors by using a Correlated Double Sampling circuit,
but in some CMOS image sensors this is not possible. The equation for reset noise, when
expressed in electrons, shows that lower gain settings, ie higher DN/e- values decrease
this noise. Hence the read noise falls with increasing ISO.
What is best for imaging? Well it depends on the type of imaging you do. Most SLR’s are
employed in RGB imaging, as they contain a bayer CFA. They are also used for lunar,
solar and planetary use too. These fields have sufficiently bright images/objects, whereby
the total noise produced by the sensor is far greater than the read noise. This scenario
would be typical for DSO imaging of the brighter targets, and is definitely true for lunar,
solar and planetary work. So in this regard the read noise is not the biggest noise
contributor. For DSO imaging I would be inclined to use ISO200 or ISO400, where there
is a good trade off between read noise and full well. If you are imaging high dynamic
range objects, or very bright objects that are easy to overexpose, like the moon, then I
would use all the dynamic range I could find. Thus ISO 100 offers me this. I can think of
only one situation where an image would be read noise limited, and that is narrowband
imaging. These filters can cut out background sky glow to very small levels such that the
shot noise associated with the sky glow can actually be less than the read noise. Imaging
a faint target in narrowband filters, especially S[II] or O[III] may result in the combined
shot noise of the target itself and the background shot noise being less than the read
noise. Imaging at ISO1600 in this situation may be of better use as the lower read noise
will enable a higher SNR, and the low full well isn’t a great issue because you wouldn’t
get near these signal levels. ISO800 may work well also. For the measured 9.4e- read
noise at ISO 1600 the signal from the target combined with the skyglow would have to be
less than approximately 100 electrons to be read noise limited. Even with narrowband
imaging it is possible, even probable that this signal level will be exceeded.
Thanks for reading
Paul Kent
15/09/09