Preparing data for the Wipe module

It is of the utmost importance that Wipe is given the best artefact-free, linear data you can muster.

Because Wipe tries to find the true (darkest) background level, any pixel reading that is mistakenly darker than the true background in your image (for example due to dead pixels on the CCD, or a dust speck on the sensor) will cause Wipe to acquire wrong readings for the background. When this happens, Wipe can be seen to "back off" around the area where the anomalous data was detected, resulting in localised patches where gradient (or light pollution) remnants remain. These can often look like halos. Often dark anomalous data can be found at the very centre of such a halo or remnant.

The reason Wipe backs off is that Wipe (as is the case with most modules in StarTools) refuses to clip your data. Instead Wipe allocates the dynamic range that the dark anomaly needs to display its 'features'. Of course, we don't care about the 'features' of an anomaly and would be happy for Wipe to clip the anomaly if it means the rest of the image will look correct.

Fortunately, there are various ways to help Wipe avoid anomalous data;

• A 'Dark anomaly filter' parameter can be set to filter out smaller dark anomalies, such as dead pixels or small clusters of dead pixels, before passing on the image to Wipe for analysis.
• Larger dark anomalies (such as dust specks on the sensor) can be excluded from analysis by, simply by creating a mask that excludes that particular area (for example by "drawing" a "gap" in the mask using the Lassoo tool in the Mask editor).
• Stacking artefacts should be cropped using the Crop module. Please note that some stackers (e.g. Deep Sky Stacker) can create single column/row pixel stacking artifacts which are easy to miss without zooming in and inspecting the edges of your dataset.
  

Bright anomalies (such as satellite trails or hot pixels) do not affect Wipe.

Edge located dark anomalies

Stacking artefacts are the most common dark anomalies located at the edges of your image. Failing to deal with them will lead to a halo effect near the edges of your dataset.

Non-edge located dark anomalies

Dust specks, dust donuts, and co-located dead pixels all constitute dark anomalies and will cause halos around them if not taken care of. These type of dark anomalies are taken care of by masking them out so that Wipe will not sample their pixels.