Saturday, June 1, 2013

Measuring white balance

With my scope finally working again, I started by determining the white balance in my hyperstar setup using the instructions from starizona. Took 3 images of 20LMi (a G3 star). It turned out to too tricky to get the mean brightness value for the stars in those images.

I wanted to do an alternative way and used eXcalibrator. eXcalibrator needs coordinates stored in the fits image. TheSkyX should store these automatically. But somehow they are not. With the help of http://nova.astrometry.net/, I plate solved my images and could download a fit image with the coordinates written in. With that, I get the following parameters:

Red: 1
Blue: 1.970
Green: 1.662

This is still high in red - but that could be the result of being in such a light polluted area where we have a lot of the orange glow from the street lights. Well, let's try it.

I took 10x7.5min RGB exposures (binned 2x2) and 10x10min L exposure (binned 1x1) of M51.

Here are the RGB images and histograms:
Red:
Green:
Blue:
You can clearly see the sky glow in the red image and in the histogram. Now, when I combine all three colors with the luminance image without any color correction, I get the following:

It wasn't clear (at least to me) from the histograms how dominant the red would be.

If I use the color correction values from above when combining the images I get this one:

So, as extreme as these color correction values seemed, in my light flooded area, they seem to be pretty accurate!

I posted about this on the ccd-newastro Yahoo! group and some folks pointed out that I shouldn't fix my sky glow issues with color calibration. Ron Wodaski gave a very good explanation of the difference of color imbalance and bias.

The problem with my (very high) calibration values was that they were derived from captured images, i.e. they did not only contain the color imbalance from my imaging setup but also the bias from the sky glow!

So, for now, I have to combine the RGB images with the same weights and then neutralize the background. Doing that results in this:
This image seems to have more natural colors then the previous one (which was very blue).