Astrophotography – Image Processing

This is the fifth part of the series on Astrophotography.

This part 5 is an introduction to image processing and the unique demands that Astro Photography (AP) generates for a wide variety of reasons.  I am going to do a simplified view of the processing of images and talk a bit about image calibration, color accuracy, light pollution and gradients in images and how to overcome those problems when using a DSLR.

The finished image is 120 frames.
Click for an enlargement

Abbreviated OSC.  An OSC is any camera with a sensor that has a Color Filter Array on it such as the well know Bayer array that is used in Nikon sensors and other arrays such as the Fuji X-Trans CFA.  The main thing both CFA’s do is allow software such as Photoshop to read a RAW file and generate the colors captured in the image by interpolating the relative light levels captured at a given pixel with the surrounding pixels.

The problem with OSCs for AP is that they are relatively very broad band in what they allow through their first filter, often referred to as the hot filter.  The hot filter is designed to remove a variety of wave lengths that would cause your RGB image to look quite strange color wise to the human eye – to give you an idea of that limitation of the eye, we see roughly 1/10 trillionth of the spectrum – i.e., we are  basically blind to the universe around us.  

OSCs work great for daytime photography and even shooting at night in lit areas, not so well for deep sky imaging.  The reason is they are a compromise.  The narrower the hot filter on an OSC, the more certain wave lengths we like to see in daytime photography get clipped.  But this allows light pollution wavelengths to aggregate during a long exposure as it is an additive effect the longer you expose.  There are filters to address this, but at this point, I have not used them so cannot comment on how well they help.  Plus, the more you filter, the longer or more subs you must take as you will wind up filtering out some useful light as well as the wavelengths you don’t want, effectively reducing the Signal to Noise Ratio, (SNR) per subframe.

Since many of us wind up imaging in our backyards, you will most likely have to deal with light pollution to some degree or another, depending on where you live.  There is an excellent website that show what sort of light pollution zone you live in shown below [1].  You can use that link to visualize the zone you live in.