The allure of taking pictures of objects in the night sky is a
powerful attraction to many amateur astronomers. Whatever the
equipment base, there is a desire to optimize the results. While
there have been many articles and books on the subject of
processing, in Adobe PhotoShop® for example, precious little has
been written about acquiring the image. If the quality of the
acquired data is not optimized, the processed result can never
correct poor data.
There are some fundamental techniques that, once understood, can
significantly improve results. Essentially there are only three
things we need to do to get good images – focus, track and expose.
Sounds simple, doesn’t it? This is not unlike what we do with a
conventional camera when we are trying to photograph a moving
target. But when it comes to starlight, the problem gets a lot more
involved for a number of reasons and we need to use a computer to
solve these problems dynamically.
We have all experienced focusing for visual use. We adjust the
focuser using a back-and-forth movement of the focuser to achieve as
sharp an image as seeing will allow. After a little experience, we
get a feel for a given telescope and eyepiece and can “snap” the
object into focus, to the degree the atmosphere (“seeing”) allows.
We all know how critical focus is to see detail in an object. The
better the focus, the more we can see. In fact, many objects can’t
be seen (“detected”) if the telescope is far out of focus. How much
of the object we see (“signal”), is directly dependent on how good
the focus is. After viewing it for a while, we move on to another
object and repeat the process. We generally don’t notice if the
focus point changes or even if it does, it is no big deal since we
can easily enough refocus it by viewing the object through the
Focusing is a whole different thing when it comes to CCD imaging.
First off, we can’t see exactly what the camera sees in real time.
Regardless of how fast a camera can take an image and present it on
the computer screen (“downloads”), it is never fast enough to
achieve that “snap” focus we get by eye. Thus we have to resort to
more elaborate techniques by using the computer to see what the
camera is seeing and adjust the focuser appropriately. Thus we need
a way for a computer to control the focus, a focusing program on the
computer to focus and a camera control program to control the
Secondly, a CCD camera is incredibly sensitive. We count individual
photons with the camera, not the thousands of photons per second we
see by the naked eye or the millions of photons per second we see
during daylight. So to get the night time signals to a reasonable
level so that it can be detected, we need to take very long
exposures. Total exposure time for the moon can be as short as ¼
second. For deep sky imaging of faint galaxies, it can be many
hours! In order to maintain the ability to detect these weak
signals, we need to insure focus is maintained, once achieved.
Focus changes due to a number of things. If we put an optical filter
in between the telescope and eyepiece, perhaps to reduce light
pollution, we refocus the telescope, never knowing or caring whether
the focus point changes. If the aluminum tube of the telescope
contracts as the evening cools down, and they all do, the focus
point shifts and we have to refocus. Some telescopes, especially
larger ones, will slightly change focus as the telescope changes its
orientation, due to mirror movement, tube flexure and other factors.
These factors become important during the typical long exposures we
take with a CCD camera.
Given the length of the exposures and the fact that we use different
filters to develop color images, we need to either insure focus is
unchanging over temperature, telescope position and filter selection
or make periodic adjustments to focus. The former is most difficult
to achieve even with expensive telescopes and special filters
(called “parfocal”, which means the focus point is unchanged with
different filters). For high quality imaging, some sort of focusing
during the evening is used by amateur and professional observatories
So let’s summarize our focusing challenge:
Initially focus using something other than our
eye with a camera that doesn’t give the immediate feedback our
eye/hand system requires when we are operating visually.
Insure the focus is stable for long periods of
time in which temperature and telescope orientation can change.
Maintain focus as different filters are inserted
between the telescope and the camera.
Tracking refers to the telescope’s mount tracking a stellar object
as it moves across the sky. As anyone who has ever observed through
a telescope without a tracking mount can tell, objects really seem
to go flying out of the field of view (“FOV”) pretty quickly. The
views from the top of the ladder on a big Dobsonian are spectacular
but fleeting. For more modest size telescopes, mounts have motors
and appropriate control electronics that track the night sky by
moving at the stellar (“sidereal”) rate. Of course, we need to align
the mount to the north celestial pole (“polar alignment”) but once
we do, we can achieve somewhat stationary object in the eyepiece.
With good polar alignment and a tracking mount, we can observe an
object for as long as we wish.
However, for CCD imaging, the problem gets more complex. If the
tracking and polar alignment is not perfect, and it never is, the
images will smear (“trail”) during long exposures. The demands of
CCD imaging on the telescope mount are much higher than for visual
High end amateur and professional systems get around this limitation
by a number of sophisticated techniques. One way consists of
modeling the pointing error of the telescope all over the sky, which
includes the polar alignment error, and adjusting the pointing based
on this model. The pointing model can be extended to tracking by
using similarly advanced techniques so that the tracking rate can be
adjusted so that, based on the model, the object can remain
stationary on the camera for extended periods of time. If the system
resolution (See Exposure, below), is not too high, then successful
imaging can be achieved. This type of imaging is called Unguided
For more modest equipment sets, good results can be achieved by a
technique called “guiding”.
Guiding consists of using essentially two cameras. One camera, the
“imager”, looks at the object you wish to image. A second camera,
the “guider”, looks at a specific reference star. By connecting the
telescope mount to a computer and connecting the guider to a
computer and having a suitable guiding program, we can begin to
solve this problem. The guider looks at a specific star, the “guide
star” and notes its position on the guider camera. We calibrate the
guiding program so that we know how much the guide star moves in
response to a specific command from the guiding program to the
telescope. Then we start the guiding program to track the guide
star. As the guide star moves, the guiding program attempts to move
the telescope in a direction to bring the guide star back to its
original position. This is the basic process of guiding.
There are two basic ways of implementing guiding, at least at the
amateur level. Here are the basic techniques:
Self-guider: Here the guider camera and the imaging camera share the
same telescope optical path. The guider camera samples a portion of
the light outside of the imager’s FOV. SBIG has a patent on a unique
arrangement in which the guider and imager are in the same housing.
This arrangement provides an all-in-one package.
Off-Axis Auto-guider Configuration
Guide Scope: There the guider looks through a small telescope
(“guide scope”) that is hard-mounted to the main scope. The imager
looks through the main scope.
External Auto-Guider Configuration
Professional techniques get considerably more sophisticated and will
not be discussed here.
An autoguider has one additional problem. Since the guider is behind
any filters, the guide star signal will be reduced depending on the
filter in place. This is usually addressed by either selecting a
sufficient exposure time for the lowest transparency filter or
manually adjusting the guider exposure depending on the filter
We know that when we look at an object that is low on the horizon,
we don’t see as well as when the object is overhead. This is due to
the amount of atmosphere (“air mass”) we are looking through.
Planetarium programs give the air mass of an object for various
altitudes normalized to a value of 1 at the zenith. It is
instructive to see how the air mass changes as an object gets closer
to the horizon. An air mass of 2 indicates we are looking through
twice as much atmosphere as at the zenith and occurs at an altitude
of 45°. The effect of the atmosphere can be seen with the naked eye
if you look at a bright star that is close to the horizon. The star
seems to flicker and even change color. This is nothing more than
the atmosphere acting as an optical element (“refraction”) changing
the position and color of the star as the atmosphere moves. To take
good images, we need to be imaging through the least amount of
atmosphere as possible, consistent with exposing for long times of
The problem here is that the meridian bisects the region of least
atmosphere. This is one of the reasons most professional
observatories use a variation of a fork mounted telescope. With this
design, it is possible to image continuously through the meridian.
Of course such precision fork mounts are quite expensive as they are
difficult to construct. At this point in the development of amateur
equipment, the most cost effective mount style, in terms of
precision per unit cost, is the German equatorial mount (“GEM”).
Fork Mounted Telescope
German Equatorial Telescope Mount
When tracking an object from east of the meridian, something must be
done when the meridian is reached with a GEM. Manual operation
consists of stopping until the object has crossed the meridian. Then
the user reacquires the object from west of the meridian. This is
called “flipping the meridian”. A typical GEM will slew to the
direction of the north celestial pole and come back from the west to
the target. In the course of doing this, the object will be rotated
180°. If the user is doing guided imaging, the guider must be
recalibrated. If the user is using a self-guider, the assembly must
be rotated by 180° to reacquire the guide star and then the guider
must be recalibrated. As a consequence, most guided imaging is not
done through the meridian. Even with unguided imaging, the images
taken west of the meridian will be rotated 180° from those taken
east of the meridian. Motorized rotators are available that can make
part of this easier but they all still require user intervention.
Let’s summarize our tracking challenges:
When we look at an object visually, a lot of natural technology is
taking place. The brightness sensors in the eye (“rods”) are
accumulating intensity (“luminance”) information. The number of rods
determines the detail (“resolution”) of what we see. The longer we
look at something, the more detail we see. This is the result of the
eye-brain system accumulating or integrating the photons that
impinge on the retina over time. This is why the longer we look at
something, the more detail we see. The eye is also averaging the
atmospheric movement (“seeing”) to bring out more detail.
Now, when we look at an object that is bright enough to stimulate
the eye’s color sensors (‘cones”), a more complex process takes
place. There are three types of cones which are, broadly stated,
sensitive to specific colors, nominally red (“R”), green (“G”) and
blue (“B”). Again, through the eye-brain system, the signals from
these sets of cones are combined in the brain to what we see as
color. Through the relative addition of the RGB cones, we “see”
color. This is an additive system that is best illustrated by the
Additive Color System
Some basic relationships can be seen here. Red plus green gives
yellow. Red plus blue gives magenta. Blue plus green gives cyan. Red
plus green plus blue gives white.
Additionally, we have a lot more rods than cones so we have more
resolution capability in black-and-white (luminance) than in color.
Electronic imagers attempt to emulate the eye’s basic technology. We
effectively replace the rods with an array of sensors (“pixels”, a
contraction of picture elements). The number of pixels determines
how many points we can see on the image. We use the same array in
combination with R, G and B filters to simulate the cones. Unlike
the eye, with this arrangement we have all the pixels available for
each color and can get the maximum resolution through each color
filter. In principle, we could take three images, one through each
filter, and have a nice, color image. Unfortunately it isn’t that
simple. Here again, we take our cue from nature.
The RGB filters are less transparent than the clear or luminance
filter so the signal is weaker. For dim images, we take luminance
exposures and data filtered through RGB filters. This is called an
LRGB image. We trade off resolution for sensitivity when taking RGB
data but not when taking L data. Of course for bright images, we can
take the RGB data at maximum resolution and simplify our remaining
tasks a bit.
With certain assumptions, we can make the resolution/sensitivity
trade-off by combining a number of pixels into one “super-pixel”.
This technique is called “binning”. 2x2 binning, means we have
combined 4 pixels into one super-pixel; 3x3 binning means we have
combined 9 pixels into one super-pixel. 1x1 binning is another term
for unbinned. For dim objects, the L data is binned 1x1 and the RGB
data is binned 2x2.
(I have moved from speaking of images to speaking of data. What
comes from a CCD imager is a string of digital data in the form of a
computer file that has to be properly calibrated and in many cases
assembled with other files to get to a picture. This is a more
appropriate term as will become apparent.)
The next question is how long the exposure should be. The longer
your exposure is, the more signal you get. This is akin to looking
in the eyepiece longer and seeing more detail. With CCD imaging
however, there are many factors at work that conspire to limit your
exposure time. Some are due to the imperfect nature of the equipment
and just occur. I will list them here but to explain them all in
detail is beyond the scope of this document. See the references at
the end for further information.
Dark current: This builds linearly with exposure time, is a
function of the CCD imager’s temperature and contributes noise to
the image. If the dark current saturates, it can not be calibrated
Saturation: If the exposure is too long, portions of the object
can saturate, causing a loss of information in the saturated region.
MFO’s: Miscellaneous flying objects, such as airplanes,
satellites, cosmic rays. The probability of an MFO crossing your FOV
increases the longer your exposure time.
Cosmic ray hits: This manifests itself as a bright spot on the CCD
imager and is more severe at higher elevations.
Tracking: The longer your exposure time, the longer your mount has
to track accurately or the longer your guider has to guide
accurately without a reset.
These limitations are surmounted by taking a number of shorter
exposures (“sub-exposures”) and then combining them in an
So why not take a large number of short images? For bright objects,
this is a good option but for dim objects, we are limited by one
over-arching characteristic of the CCD imager – readout noise.
Recall we spoke of data above. Each pixel can have a specific value
but determining that value has an uncertainty in measuring or
reading that value. That uncertainty is called noise. If you look at
a weak TV signal, you see what is sometimes called “snow”. That is
noise, due to the signal not being strong enough. Similarly, you
hear static when you listen to a distant signal on the radio. Every
time we measure the data in a pixel, there is some uncertainty,
noise that comes primarily from the electronics used to measure the
pixel. This is called readout noise and is a major limiting factor
on any CCD imager. Low values or readout noise are sought since they
determine a number of key performance parameters, one of which is
how short an exposure can be.
Thus a strategy emerges. You want to expose long enough so that
readout noise is not a problem but short enough to minimize the
previously mentioned problems. There is a trade-off that depends on
a number of factors.
First, how bright is your sky (“sky glow”)? Sky glow brings its own
noise due to the uncertainty in the arriving photons. So, if your
sky glow is much larger than your readout noise, then there is
little value in exposing longer. What are the characteristics of
your CCD imager? By these key characteristics, you can determine an
optimal sub-exposure length. Here are the factors you need to make
Sky glow: The brightness of your sky background in electrons per
g: The gain of your imager in electrons per ADU (e/ADU)
Ron: The readout noise of your imager in electrons (e)
A calculator is available to lead you through the determination of
your optimal sub-exposure length here:
CCD imaging chips are not perfect. There is a sensitivity difference
from pixel to pixel. This difference gives rise to what is called
“hot” and “cold” pixels. Hot pixels accumulate signal much faster
than average and cold pixels accumulate signal much slower. Thus an
image of our data will have a number of “salt and pepper” effects
that will detract from the image. Also our imperfect camera may have
some other low level artifacts that are a function of electronic
limitations that will limit how low in signal we can go. While the
hot and cold pixels can be somewhat relieved by processing, there
remains “warm and cool pixels” that become hard to distinguish from
the desired object. These imperfections can be lumped under the
title of “pattern noise”.
A technique to minimize this effect is called dithering. The scope
is moved very slightly between images. When the sub-exposures are
aligned and combined, the pattern noise does not line up. Assuming
the scope is moved appropriately and the sub-exposures are combined
properly, the pattern noise is either eliminated or greatly reduced.
Calibration consists of removing predictable factors from our image.
Because of our imperfect CCD imaging chip, we have to contend with
dark current as described above. Additionally, most telescopes do
not have a perfectly uniform light transmission across their FOV.
This is generally not detectable by eye but is easily detectable by
a CCD imager. Each of these effects can be reduced by the process of
Dark current is removed by arithmetically subtracting a master dark
frame from the sub-exposure. A dark frame is an exposure made at the
same camera temperature as the light sub-exposure and for the same
duration as the sub-exposure. A master dark frame is obtained by
combining a suitable number of individual dark sub-exposures. The
optimal number is determined by the calculator mentioned above. Each
pixel of the master dark frame is subtracted from each pixel of the
light frame to remove the dark current.
Light uniformity is corrected by arithmetically dividing a
normalized reference flat field. The flat field is obtained my
aiming the telescope at a uniform light source and taking an
exposure, making sure the camera is operating in its linear range.
Many use artificial light sources such as light boxes, screens, even
T-shirts! But there is an available light source that has been shown
to be sufficiently uniform for many professional and probably all
amateur purposes – the twilight sky at dawn or dusk. There are some
complexities in using the twilight sky. First, the sky brightness is
changing relatively quickly. Secondly there is only one optimal
location for maximizing uniformity. So one has to move fast and
continually adjust exposures to stay in the linear range of the CCD.
Typically a number of flat field frames are taken to reduce noise
(master flat) and a set is taken through each filter for maximum
Calibration consists of creating master dark and flat frames and
doing the appropriate arithmetic on a pixel by pixel basis for each
Ready to go, right?
Let’s assume you want to get the best final image that sky
conditions and your equipment allow. You have your scope set up and
polar aligned. Your camera is cooled and ready to go. Your telescope
is connected to your computer and tracking. Your focuser is
connected and you have focused your system. Your object is framed as
you like it. If you are doing guided imaging, your guider is
calibrating and happily guiding along.
Now that you know your sub-exposure time, you can begin to take a
number of sub-exposures, perhaps through each filter. You should
focus frequently to make sure you remain in focus. Each time you
change a filter you should of course refocus. You should adjust your
guide exposure consistent with each filter. Of course, you should
move your telescope slightly between each exposure to minimize
pattern noise. When you come to the meridian and are using a GEM you
can go to the other side, rotate the camera, reacquire a guide star,
recalibrate and continue imaging. And when you’re done with your
imaging, don’t forget to take your dark calibration data and flat
fields. You did turn off your guider and park your scope, right? You
need to get enough of each and, in the case of flats, don’t forget
to take them for each filter for best results. If you want the best,
use the morning sky and be ready and alert to un-park your scope,
point to the right spot, select the filter and change the exposure
as needed. Don’t forget to park your scope and turn off your camera
cooler and close the dome.
This sounds awfully tedious. What if I miss a step or forget
something? How can I be sure to do all this as the night wears on
and the coffee wears off? Can I only image when I don’t have to work
the next day? Is there any way to make this easier? You bet!
Let’s look at the features of CCDAutoPilot aligned with the above
challenges and tasks to getting the best image you can with the sky
conditions you have and the equipment you are using.
Focusing - CCDAutoPilot
Focus offsets for each filter
Focus after each filter change
Focus periodically on a chosen star outside the
Tracking and Guiding -
CCDAutoPilot Core Features
Dark/Bias calibration frames
- CCDAutoPilot Core Features
Flat Fields -
Automatic dawn and dusk flats
Auto-exposure to target ADU level
Specify the number, filter and binning
Goes to the right spot on the sky automatically
Takes as many flats as quickly as possible
Can also be used with artificial sources (light
CCDAutoPilot Core Features
CCDAutoPilot is an application that arises from my desire as a CCD
imager for high quality results. I wanted to get the best possible
results from one or many evenings of imaging a target. It represents
the culmination of 3½ years of programming for imaging acquisition
that introduced for the first time many acquisition firsts in an
easy-to-use point-and-click interface with application independence.
The CCDAutoPliot2 development team is proud of our history of
innovation. We will continue to bring new techniques and
technologies to the amateur CCD imaging community to help you
achieve the highest quality for your time and effort.