Processing of Astronomical CCD Images

The key to processing images is to have a clear idea of your objective. Do you want to produce "a pretty picture" or bring out some specific detail or feature of the target object? Is colour important or will black and white be sufficient?. With a clear objective in mind consider the various types of processing possible.

Calibration

Calibration is the process of removing unwanted signals from the raw images. Calibration is described here and it is assumed that all the images are first calibrated prior to further processing.

Quality Assessment

You will want to select only the best of your captured images for processing. The best way is to look at each image and discard those that are not clear, sharp, well shaped etc. Even with video it can be worth the time to go through and select just a few really good frames rather than rely on the 'quality' ranking provided by your processing software.   

Resampling (Resizing)

You may wish to enlarge the images by a factor (say x1.5 or x2.0). This will not improve the level of detail in each image but it will spread the detail over more pixels. This may be of benefit by allowing the alignment and stacking process (see below) to achieve "sub pixel" precision so that the resulting stacked image has finer detail than any of the original images. An enlarged image may also work better with sharpening filters such as Registax's wavelets or the Unsharp Mask. Resample (resize) back to the original (or any other desired) size later in processing.

Alignment

You will have captured multiple images (or a video) of your target object. All frames will need to be aligned and stacked. Alignment is the process of shifting each image up/down and left/right so that the target object is in exactly the same place on every image. There are several ways of doing this provided in astro-imaging software:

  • Manual: You have to click in exactly the same place (e.g. a star) in each image to set the alignment point.
  • Centroid: You click on the same star in each image and the software will try to align the centre of the star.
  • Automatic: (e.g using FFT algorithm) you select a suitable star or image feature and the software will do its best to align the feature on each image.

Some software will allow you to select two points in each image and will rotate the images to compensate for images taken using an alt/azimuth mounted telescope. Registax allows you to select multiple points in the image and can align different areas of the image differently. This can be quite useful when poor "seeing" has caused areas of the image to shimmer.

For video, manual alignment is usually impractical because of the number of frames. I normally use use Registax for videos. For still frames I like to use Centroid (Maxim) or Automatic (Registax). 

Stacking

Once the images have been aligned then they can be stacked by:

  • Averaging (Median): This is the normal way to stack images. Each pixel is set to the median value of the appropriate pixels from all the images. Noise is effectively reduced by averaging and there is no danger of any pixels becoming saturated.
     
  • Adding (Sum): The images are added together and pixel values are the sum of the appropriate pixel on all the images. Generally this is not a good idea as bright spots (e.g. stars) will add up to more than the maximum value of a pixel causing distortion or "white out" or areas of the image. But if you have a limited number of images and their maximum pixel values are low then adding can be a useful because it will give a greater range of pixel values for subsequent contrast enhancement.
     
  • Drizzle: This is a technique designed by NASA to sharpen images acquired by the Hubble Space Telescope. The objective is to combine the information in multiple images to get a better resolution than the number of pixels in the camera. It is only relevant when the resolution of the telescope is better than the resolution of the CCD. There is a detailed description of the process here. The new Meade DSI image processing software (Autostar Envisage) has an implementation of Drizzle and I also use the one in Registax. The output image is larger than the input image thus possibly may have better resolution than individual input images.  (Personally I get more success using simple x1.5 resampling rather than Drizzle).

Contrast and Colour

First check this discussion about colours.

Colour plane alignment

If you have a colour camera or have produced a colour image from (L)RGB images then examine the stacked image carefully to see if the colours are correctly aligned. When taking images of objects near the horizon the red, green and blue images may be slightly displaced. This will cause a red tinge on one side of a star/planet and a blue tinge on the other side. Your software should provide the ability to shift the RGB components and get them properly aligned.

Stretch, Gamma, Balance, Hue and Saturation

Once you have a stacked image, adjust contrast and colour according to the results you require. The most frequently used techniques are:

  • Stretch: This resets the top and bottom of the range of pixel values and 'stretches' the range of pixel values in your image. Gradually increase the 'minimum' pixel value until the dark sky background is reasonably black. Gradually reduce the 'maximum' pixel value until bright stars or planetary features are bright but not saturated.
  • Contrast & Brightness: This has the same effect as 'stretch' but the controls are different. Gradually increase contrast and adjust brightness to obtain a dark sky and bright stars.
  • Gamma: This allows you to increase or decrease the brightness of mid-range pixels without changing the minimum and maximum values. It is useful to accentuate shadows in a planetary image, bring out faint nebulosity or increase the brightness of small stars in a cluster.
  • Histogram: This combines stretch and gamma adjustments in a flexible way. You are shown a graph of input-pixel-value and output-pixel-value. To start, the graph is a straight line but you can set it to any shape. The classical "S" shaped curve is often the most effective at bringing out the best in an image. It pays to experiment.
  • Colour Balance: If the image has too much red, green or blue in it then a colour balance correction can be applied.
  • Saturation: If the image has too little or too much colour then an increase or decrease in saturation can be applied.
  • Hue: This will shift the colour of all pixels towards one or other end of the spectrum; generally not a good idea unless you want to create false colour effects.   

It is usually best not to make too dramatic a change in an image in one go. Gradually improve the image using a series of contrast and colour adjustments interspersed with sharpening and noise reduction filters (see below).

Filters

Most software will provide a huge range of filters and using the right filters is a key skill in image processing. I will mention just a few here.

Sharpening Filters

The objective is to make stars small and bright and to bring out detail in planetary images. Fuzzy edges need to be made less fuzzy.

  • High Pass: (Sharpen) Accentuates the high frequency signals in the image. Makes changes in brightness across the image more stark. Can also accentuate the noise.
  • Unsharp: The unsharp mask is one of the most powerful filters for sharpening an image. The image is examined to find edges and for each pixel near an edge a decision is made as to whether it is on the dark side or the light side. Thus fuzzy edges are removed. There are usually three controls:
    • Radius: set this to your best guess as to how many pixels wide the fuzziness is at the edges of stars or features. Adjust up/down for best results.
    • Strength: set this to determine how extreme the lightening/darkening of pixels will be near edges. Too much will introduce noise or dark rings round stars.
    • Clipping: set this to a value above zero to reduce noise. This control says in effect "if you find a change in pixel value less than clipping value then this is not actually an edge so don't try to sharpen it" 
  • Wavelets: The wavelet filter like that found in Registax is a complex but effective tool. The signal in the image is examined at different frequencies and you can chose how much of each frequency you want. Best is to read the Registax documentation and experiment with it.
  • Deconvolution: There are a number of 'deconvolution' filters such as Maximum Entropy Deconvolution. The theory is complicated but the idea is that if you know (can guess at) the way in which fuzziness was introduced then you can remove it by a series of repetitive processes.  I have had some limited success sharpening star clusters with this type of filter but more often than not it seems to just make a mess of the image!
  • Erosion: This filter cuts away at bright edges. The effect is to reduce the size and 'sharpen' stars. This can be useful if large bright stars are spoiling the view of a galaxy or nebula. In fact multiple use of erosion can remove the stars completely! However, remember that the resulting image is not 'correct' and should not be presented as such.

Noise Reduction Filters

If the image is 'grainy' this is due to random noise. The best way to avoid noise is to average lots of images, but assuming that has been done already then try some filters:

  • Low pass: This reduces high frequency signals in the image and can reduce the effect of pixel-to-pixel noise. However it may make the image too fuzzy.
  • Median/average: This will set pixels to the median or average value of the pixels in a given radius around them and can reduce high frequency noise. Unfortunately it also reduces detail.
  • Edge preserving smooth: In the same way that the unsharp mask looks to accentuate edges this filter looks for edges and smoothes out those areas that are not near an edge. This often works quite well to reduce noise without reducing detail.
  • Despeckle/Hot Pixel: can be used to remove hot pixels.

Specialist software (e.g. Neat Image)  has really powerful algorithms for removing noise.  

Other Filters

Most photo-editing software provides a huge range of filters and effects designed for 'artistic' or photographic effect. Most of them are unsuitable for astronomical images - but by all means experiment with them.

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Tony Evans 2004-2014

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