A short introduction to astronomical image processing
 |
| Figure 1: An image —
an array or a matrix of pixels arranged in columns and rows. |
 |
| Figure 2: Each pixel has a value from
0 (black) to 255 (white). The possible range of the pixel
values depend on the colour depth of the image, here 8 bit
= 256 tones or greyscales. |
|
|
| Figure 3: A true-colour image assembled
from three greyscale images coloured red, green and blue.
Such an image may contain up 16 million different colours. |
|
|
| Figure 4: the additive model of RGB.
Red, green, and blue are the primary stimuli for human colour
perception and are the primary additive colours. Courtesy
of adobe.com. |
|
|
| Figure 5: The colours created by the
subtractive model of CMYK don't look exactly like the colours
created in the additive model of RGB Most importantly, CMYK
cannot reproduce the brightness of RGB colours. In addition,
the CMYK gamut is much smaller than the RGB gamut. Courtesy
of adobe.com. |
|
|
| Figure 6: This illustration clearly shows
the different gamuts of the RGB and CMYK colour spaces. The
background is the CIE Chromaticity Diagram (representing the
whole gamut of human colour perception). Courtesy adobe.com. |
|
|
| Figure 7: Filter list for Hubble’s
WFPC2 camera (Wide Field and Planetary Camera 2). Filter names
are to the left (names include approximate wavelength in nm)
in column 1. Column 5 contains the physical property of the
radiation the filter lets through. Column 7 is the
central wavelength. The N’s and W’s are short for
Narrow and Wide. |
|
|
| Figure 8: Example of an image constructed
from narrow-band exposures. Since the narrow-band exposures
probe individual atomic transitions the result is an image
that has very ‘sharp’ features. |
|
|
| Figure 9: A broad-band image of the “Hyperactive
galaxy NGC 7673”. |
|
|
| Figure 10: An example of an image constructed
from 7 broad-band filters all the way from ultraviolet (left)
to infrared (right). |
|
|
| Figure 11: An example of how a colour
image is constructed from four broad-band filters (seen from
the side in 1.): blue, green yellow and red. When the images
are overlaid (2. and 3.) the resulting image (4.) is a colour
composite. |
|
|
| Figure 12: An example of an enhanced
colour image (not in chromatic order): Sometimes it is necessary
to break the ‘rules’ for image processing. Here
the Hydrogen-alpha filter is coloured blue instead of the
red colour it is in nature. This is an example of a so-called
false-colour image, where the blue was chosen for aesthetic
reasons. |
|
|
| Figure 13: Sequences in the production
of a Hubble Space Telescope image of Messier 17. First the
individual exposure (taken through three different filters):
1. 673n (Sulphur) shown in red in the final image), 2. 656n
(hydrogen, green), 3. 502n (oxygen, blue), 4. First colour
composite attempt, 5. Improving, 6. Improving, 7. Improving,
8. Adjusting the composition and then 9. Final colour and
contrast adjustments for the final image. |
|
|
| Figure 14: The difference between two
stretch functions. To the left is a linear representation
of the pixels and to the right a logarithmic. It is seen that
the log lowers the contrast too much and therefore is not
the aesthetically desirable function to choose here. |
Available as a PDF-file here.
What is an image?
An image is an array, or a matrix, of square pixels (picture elements)
arranged in columns and rows.
In a (8-bit) greyscale image each picture element has an assigned
intensity that ranges from 0 to 255. A grey scale image is what
people normally call a black and white image, but the name emphasizes
that such an image will also include many shades of grey.
A normal greyscale image has 8 bit colour depth = 256 greyscales.
A "true colour" image has 24 bit colour depth = 8 x 8 x 8 bits
= 256 x 256 x 256 colours = ~16 million colours.
Some greyscale images have more greyscales, for instance 16 bit
= 65536 greyscales. In principle three greyscale images can be
combined to form an image with 281,474,976,710,656 greyscales.
There are two general groups of 'images': vector graphics (or
line art) and bitmaps (pixel-based or 'images'). Some of the most
common file formats are:
- GIF - an 8-bit (256 colour), non-destructively compressed
bitmap format. Mostly used for web. Has several sub-standards
one of which is the animated GIF.
- JPEG - a very efficient (i.e. much information per byte) destructively
compressed 24 bit (16 million colours) bitmap format. Widely
used, especially for web and Internet (bandwidth-limited).
- TIFF - the standard 24 bit publication bitmap format. Compresses
non-destructively with, for instance, Lempel-Ziv-Welch (LZW)
compression.
- PS - Postscript, a standard vector format. Has numerous sub-standards
and can be difficult to transport across platforms and operating
systems.
- PSD - a dedicated Photoshop format that keeps all the information
in an image including all the layers.
Colours
For science communication, the two main colour spaces are RGB
and CMYK.
RGB
The RGB colour model relates very closely to the way we perceive
colour with the r, g and b receptors in our retinas. RGB uses
additive colour mixing and is the basic colour model used in television
or any other medium that projects colour with light. It is the
basic colour model used in computers and for web graphics, but
it cannot be used for print production.
The secondary colours of RGB – cyan, magenta, and yellow
– are formed by mixing two of the primary colours (red,
green or blue) and excluding the third colour. Red and green combine
to make yellow, green and blue to make cyan, and blue and red
form magenta. The combination of red, green, and blue in full
intensity makes white.
In Photoshop using the “screen” mode for the different
layers in an image will make the intensities mix together according
to the additive colour mixing model. This is analogous to stacking
slide images on top of each other and shining light through them.
CMYK
The 4-colour CMYK model used in printing lays down overlapping
layers of varying percentages of transparent cyan (C), magenta
(M) and yellow (Y) inks. In addition a layer of black (K) ink
can be added. The CMYK model uses the subtractive colour model.
Gamut
The range, or gamut, of human colour perception is quite large.
The two colour spaces discussed here span only a fraction of the
colours we can see. Furthermore the two spaces do not have the
same gamut, meaning that converting from one colour space to the
other may cause problems for colours in the outer regions of the
gamuts.
Astronomical images
Images of astronomical objects are usually taken with electronic
detectors such as a CCD (Charge Coupled Device). Similar detectors
are found in normal digital cameras. Telescope images are nearly
always greyscale, but nevertheless contain some colour information.
An astronomical image may be taken through a colour filter. Different
detectors and telescopes also usually have different sensitivities
to different colours (wavelengths).
Filters
A telescope such as the NASA/ESA Hubble Space Telescope typically
has a fixed number of well-defined filters. A filter list for
Hubble’s WFPC2 (Wide Field and Planetary Camera 2) camera
is seen to the right.
Filters can either be broad-band (Wide) or narrow-band (Narrow).
A broad-band filter lets a wide range of colours through, for
instance the entire green or red area of the spectrum. A narrow-band
filter typically only lets a small wavelength span through, thus
effectively restricting the transmitted radiation to that coming
from a given atomic transition, allowing astronomers to investigate
individual atomic processes in the object.
A filename such as 502nmos.fits indicates that the filter used
has a peak at 502 nm. In the table below, you can see that this
filter is a narrow bandwidth filter, i.e. it only lets radiation
with wavelengths within a few nm of 502 nm through.
Below is an example of an image composed from narrow-band exposures.
This results in very sharply defined wisps of nebulosity since
each exposure separates light from only some very specific physical
processes and locations in the nebula.
Galaxies are often studied through broad-band filters as they
allow more light to get through. Also the processes in a galaxy
are more ‘mixed’ or complicated, result from the outputs
of billions of stars and so narrow-band filters give less ‘specific’
information about the processes there.
A figure illustrating the process of stacking together different
colour exposures is seen in figure 10.
A figure of the process of stacking together different colour
exposures is seen in figure 11 to the right.
Assigning
colours to different filter exposures
The astronomical images we see on the web and in the media are
usually ‘refined’ or ‘processed’ as compared
to the raw data that the astronomers work on with their computers.
In ‘pretty pictures’ all artefacts coming from the
telescope or the detectors are for instance removed as they do
not say anything about the objects themselves. It is very rare
that images are taken with the sole intention of producing a ‘pretty’
colour picture. Most ‘pretty pictures’ are constructed
from data that was acquired to study some physical process, and
the astronomer herself probably never bothered to assemble the
greyscale images to a colour image.
Natural colour images
It is possible to create colour images that are close to “true-colour”
if three wide band exposures exist, and if the filters are close
to the r, g and b receptors in our eyes. Images that approximate
what a fictitious space traveller would see if he or she actually
travelled to the object are called “natural colour”
images.
To make a natural colour image the order of the colours assigned
to the different exposures should be in “chromatic order”,
i.e. the lowest wavelength should be given a blue hue, the middle
wavelength a green hue and the highest wavelength should be red.
Representative colour images
If one or more of the images in a data set is taken through a
filter that allows radiation that lies outside the human vision
span to pass – i.e. it records radiation invisible to us
- it is of course not possible to make a natural colour image.
But it is still possible to make a colour image that shows important
information about the object. This type of image is called a representative
colour image. Normally one would assign colours to these exposures
in chromatic order with blue assigned to the shortest wavelength,
and red to the longest. In this way it is possible to make colour
images from electromagnetic radiation far from the human vision
area, for example x-rays. Most often it is either infrared or
ultraviolet radiation that is used.
Enhanced colour images
Sometimes there are reasons to not use a chromatic order for an
image. Often these reasons are purely aesthetic, as is seen in
the example below. This type of colour image is an enhanced colour
image.
You are the judge
When processing raw science images one of the biggest problems
is that, to a large degree, you are ‘creating’ the
image and this means a colossal freedom within a huge parameter
space. There are literally thousands of sliders, numbers, dials,
curves etc. to twist and turn.
Speaking of right and wrong, there really are no wrong or right
images. There are some fundamental scientific principles that
should normally be observed, but the rest is a matter of aesthetics
— taste. Chromatic ordering of the exposures is one of the
important scientific principles.
Stretch function
One particularly important aspect of image processing is the choice
of the best stretch function. You choose which “stretch
function” or representation to use in the Fits Liberator
window.
A logarithmic representation of the pixel values tends to suppress
the bright parts of the image, i.e. the stars, and to enhance
the fainter part, e.g. nebulosity. This can be desirable if the
‘faint stuff’ needs ‘a boost’, but a logarithmic
stretch function can also reduce the contrast in an image, producing
a lower dynamic range as is seen in the example below.
Links
www.hubblesite.org/sci.d.tech/behind_the_pictures
heritage.stsci.edu/commonpages/infoindex/
ourimages/color_comp.html
|
