Important dataset preparation do's and don'ts

There are a few simple, but important, do's and don'ts to prepare your dataset for post-processing in StarTools.

Learning how to use a new application is daunting at the best of times. And if you happen to be new to astrophotography (welcome!), you have many other things, acronyms and jargon to contend with too. Even if you consider yourself an image processing veteran, there are some important things you should know. That is because some things and best practices play a bigger role in StarTools than in other applications.

Really, these all boil down to making sure your is as virgin as possible. Note that doesn't mean noise-free or even good, it just means you have adhered to all best the below conditions and practices to the best of your abilities.

If you are new to processing

When learning how to process astrophotography images, the last thing you want to do, is learning all sorts of post-processing tricks and techniques, just to work around issues that are easily avoidable during acquisition or pre-processing. Fixing acquisition and pre-processing issues during post-processing, will never look as good, while you will also not learn much from this; it is likely whatever you learn and do to fix a particular dataset learn is likely not applicable to the next.

Conversely, if your dataset is clean and well calibrated according to best practices, you will find workflows much more replicable and shorter. In short, it is just a much better use of your time and efforts! You will learn much quicker and you will start getting more confident in finding your personal vision for your datasets - and that is what astrophotography is all about.

If you are an image processing veteran

When we say StarTools requires the most virgin dataset you can muster, we really mean it. It means no procedures or modifications must be done by any software - no matter how well-meaning. No gradient reduction, no color balancing, not even normalization (if not strictly necessary). Signal evolution Tracking - the reason why StarTools achieves objectively better results than other software - absolutely requires it.


  • Make sure your dataset is as close to actual raw photon counts as possible.
  • Make sure your dataset is linear and has not been stretched (no gamma correction, no digital development, no levels & curves)
  • Make sure your dataset has not been normalised (no channel calibration or normalisation) unless unavoidable due your chosen stacking algorithm
  • Make sure all frames in your dataset are of the same exposure length and same ISO (if applicable)
  • Make sure your dataset is the result of stacking RAW files (CR2, CR3, NEF, ARW, FITS, etc.) and not lossily compressed or low-bit depth formats (e.g. not JPEGs or PNGs).
  • Make sure no other application has modified anything in your dataset; no stretching, no sharpening, no gradient reduction, no normalisation
  • If you can help it, make sure your dataset is not color balanced (aka "white balanced"), nor has had any camera matrix correction applied
  • Flats are really not optional - your dataset must be calibrated with flats to achieve a result that would be generally considered acceptable
  • Dithering between frames during acquisition is highly recommended (a spiralling fashion is recommended, and if your sensor is prone to banding, you will want to use larger movements)
  • If you use an OSC or DSLR, choose a basic debayering algorithm (such as bilinear or VNG debayering) in your stacker. Avoid "sophisticated" debayering algorithms meant for single frames and terrestrial photography like AHD or any other algorithms that attempt to reconstruct detail.
  • If using an mono CCD/CMOS camera, make sure your channels are separated and not pre-composited; use the Compose module to create the composite from within StarTools and specify exposure times where applicable.
  • Make sure you use an appropriate ISO setting for your camera (see Recommended ISO Settings for DSLR cameras section)

Some common problems in StarTools, caused by ignoring the check-list above;

  • Achieving results that are not significantly better than from other software
  • Trouble getting any coloring
  • Trouble getting expected coloring
  • Trouble getting a good global stretch
  • Halos around dust specks, dead pixels or stacking artefacts
  • Faint streaks (walking noise)
  • Vertical banding
  • Noise reduction or other modules do not work, or require extreme values to do anything
  • Ringing artifacts around stars
  • Color artefacts in highlights (such as star cores)
  • Trouble replicating workflows as seen in tutorials and/or videos

Allowed / not allowed

Allowed in your dataset;

  • Noise grain
  • Light pollution
  • Sky gradients

Ideally avoided;

  • Vignetting
  • Dust specks, dust donuts
  • Smudges
  • Amp glow
  • Dead pixels, dead sensor columns
  • Satellite trails
  • Trees or buildings
  • Walking noise and other correlated noise (e.g. noise that is not single-pixel speckles)

Do's and don'ts


  • Process your dataset from start-to-finish in StarTools including compositing (LRGB, LLRGB, SHO, HOO, etc.)
  • Use simple workflows
  • Acquire and apply flats
  • Dither between frames during acquisition
  • Bin your dataset if your dataset is oversampled
  • Use deconvolution to restore detail if possible
  • Practice with some publicly available datasets that are of reasonable quality to get a feel for what a module is trying to do under normal circumstances


  • Do not post-process any part of your image in any way, in other application before opening it in StarTools
  • Do not make composites in any other application but StarTools
  • Do not process any part of your subs any way, in other application before stacking them
  • Do not visit the same modules many times
  • Do not process your dataset at higher resolution than necessary
  • Do not drizzle your dataset in your stacker if your dataset is already oversampled