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Quick Start Tutorial: a quick generic work flow

Screenshot of dialog from Deep Sky Stacker
Giving StarTools virgin data is of the utmost importance. For example, if you are using DeepSkyStacker, make sure 'RGB Channels Background Calibration' and 'Per Channel Background Calibration' are set to 'No'.

Getting to grips with new software can be daunting, but StarTools was designed to make this as painless as possible. This quick, generic work flow will get you started.

Step 1

Open an image. Processing in StarTools is easiest and will yield vastly better results if the data is as "virgin" as possible, meaning unstretched, not colour balanced, not noise reduced and not deconvolved. Best results are achieved with data that is as close to what the camera recorded (e.g. simple photon counts) as possible.

Do not use any software that may have meddled with the data prior to passing it to your stacking program. Avoid any pre-conversion tools or software that came with your camera. Make sure that any stacking software that you use is set up to perform as little processing to the data as possible. For example, if you use Deep Sky Stacker make sure that Per Channel Color Calibration and RGB Channels Calibration are set to 'no'. Also make sure that, in Deep Sky Stacker, the final file is saved with settings 'embedded', rather than applied.

Counter-intuitively, the output you will be after will, more often than not, have a distinct, heavy color bias with little or no apparent detail. Worry not; subsequent processing in StarTools will remove the color bias, while restoring and bringing out detail.. If, looking at the initial image leaves you wondering how on earth this will be turned into a nice picture, you are often on the right track.

A screenshot showing AutoDev highlighting problems in the data that need fixing.
In the presence of problems in your data that need fixing, AutoDev will show you exactly what they are. Here we can see stacking artefacts, some vignetting towards the corners and a 'dirty' yellow/brown bias caused by light pollution.

Upon opening an image, the Tracking dialog will open, asking you about the characteristics of the data. Choose the option that best matches the data being imported.

Step 2

Launch AutoDev to help inspect the data. Chances are that the image looks terrible, which is - believe it or not - the point. In the presence of problems in the data, AutoDev will show these problems until they are dealt with. Because StarTools constantly tries to make sense of your data, StarTools is very sensitive to artefacts, meaning anything that is not real celestial detail (such as stacking artefacts, dust donuts, gradients, terrestrial scenery, etc.). Just 'Keep' the result. StarTools, thanks to Tracking, will allow us to redo the stretch later on.

At this point, things to look out for are;

  • Stacking artefacts close to the borders of the image. These are dealt with in the Crop or Lens modules
  • Bias or gradients (such as light pollution or skyglow). These are dealt with in the Wipe module.
  • Oversampling (meaning the finest detail, such as small stars, being "smeared out" over multiple pixels). This is dealt with in the Bin module.
  • Coma or elongated stars towards one or more corners of the image. These can be ameliorated using the Lens module.

A screenshot showing AutoDev being run again on the cleaned up data
Using AutoDev ('redo') again after fixing the initial problems that AutoDev showed us before; stacking artifacts and light pollution were removed.

Step 3

Fix the issues that AutoDev has brought to your attention;

  1. Ameliorate coma using the Lens module.
  2. Crop any remaining stacking artefacts.
  3. Bin the image until each pixel describes one unit of real detail.
  4. Wipe gradients and bias away. Be very mindful of any dark anomalies - bump up the Dark Anomaly filter if dealing with small ones (such as dark pixels) or mask big ones out using the Mask editor. Use the 'Temporary AutoDev' feature to get a better idea of how Wipe is doing.

Step 4

Once all issues are fixed, launch AutoDev again and tell it to 'redo' the stretch. If all is well, AutoDev will now create a histogram stretch that is optimised for the "real" object(s) in your clean data. If your data is very noisy, it is possible AutoDev will optimise for the noise, mistaking it for real detail. In this case you can tell it to Ignore Fine detail.

If your object(s) reside on an otherwise uninteresting or "empty" background, you can tell AutoDev where the interesting bits of your image are by clicking & dragging a Region Of Interest.

Screenshot of StarTools with a processed image that has not been noise reduced yet.
The image after deconvolution (Decon), wavelet sharpening (Sharp), local dynamic range optimisation (HDR) and color calibration (Color).

Don't worry about the colouring just yet - focus getting the detail out of your data first.

Step 5

Season your image to taste. Apply some deconvolution with the Decon module, dig out detail with the Wavelet Sharpen ('Sharp') module, enhance Contrast with the Contrast module and fix any dynamic range issues with the HDR module.

There are many ways to enhance detail to taste and much depends on what you feel is most important to bring out in your image.

Step 6

Launch the Color module.

See if StarTools comes up with a good colour balance all by itself. A good colour balance shows a good range of all star temperatures, from red, orange and yellow through to white and blue. HII areas will tend to look purplish/pink, while galaxy cores tend to look yellow and their outer rims tend to look bluer.

Green is an uncommon colour in outer space (though there are notable exceptions, such as areas that are strong in OIII such as the core of M42). If you see green dominance, you may want to reduce the green bias. If you think you have a good colour balance, but still see some dominant green in your image, you can remove the last bit of green using the 'Cap Green' function.

Image showing noise reduction on one half of the image.
200% zoom with right part of the image denoised by Tracking supported Denoise, and no noise reduction applied to the left part of the image..

Step 7

Switch Tracking off and apply noise reduction. You will now see what all the fuss is about, as StarTools seems to know exactly where the noise exists in your image and snuffs it out. The main parameters to tweak are 'Smoothness', 'Brightness Detail Loss' and 'Color Detail Loss'.

Step 8

Pour yourself your favourite beverage and pat yourself on the back for a job well done!


A video is also available that shows a simple, short processing workflow of a real-world, imperfect dataset.

Please refer to the video description below the video for the source data and other helpful links.

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