Dark Frame Calibration - SBIG STF Series User Manual

3.2 Dark Frame Calibration

Every camera sensor produces a certain amount of dark current, which
accumulates in the pixels during an exposure. The dark current is produced
by heat, and high-performance cameras cool their sensors to minimize this
effect.
The main problem with dark current is that it accumulates at a different rate
in every pixel. Some pixels are "hot" and others are "cold". Unfortunately there
is usually a spattering of pixels that are especially hot, which degrade the
image a great deal. Fortunately, the effect of hot and cold pixels can be easily
removed by subtracting a dark frame.
A dark frame is an exposure taken under the same conditions as the light
exposure, but with no light striking the sensor array. Since each pixel is
consistent in its dark current at any one temperature, the dark frame can be
subtracted from the light frame to remove the fixed pattern from the image. For
most sensors this produces a striking improvement in the image.
Unfortunately, while the rate of dark current is constant, the actual
accumulation of dark current is random. Anything that is random in imaging
is noise, which is the enemy of sensitivity. Doubling the dark current increases
the random noise produced by the square root of 2 (approximately 1.414). This
means the hot pixels produce significantly more noise. Since the noise is
random and therefore unpredictable, it cannot be removed; in some calibrated
images they will be brighter than normal, and in others they will be darker
than normal. You can improve the hot pixels, but you cannot completely fix
them.
So subtracting a dark frame eliminates noise because it gets rid of the gross
pixel-to-pixel variations in dark current. Unfortunately, and perhaps
counterintuitively, subtracting a dark frame also adds noise to the image.
Every pixel has random read noise, plus the residual dark current noise. This
noise does not subtract, but rather adds in a root-sum-square fashion.
Therefore simply subtracting one dark frame increases the noise level 41%.
The way to get rid of this noise is to remove it by averaging multiple dark
frames. Every time you quadruple the number of averaged dark frames, you
drop the noise contribution in half.
Suppressing Hot Pixels
Although you can greatly improve the hot pixels by calibration, there will still
be a residual speckle of hot and cold pixels in the image. For astronomical
applications, you can "dither" the pointing of the camera slightly between
exposures, thus distributing the noise contribution of each hot pixel to a
slightly different position on the image. You can then combine a number of
images together using the Median, Sigma Clip, or SD Mask algorithm, which
will reject the hot pixel contributions altogether.
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