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Processing A Globular Cluster
Processing A Globular Cluster
The Great Globular Cluster in Hercules is one of my favorite objects. I find myself coming back to it year after year.
The techniques required to image and process a globular cluster are quite different from those needed for deep sky objects.
My goals for this image were to obtain the sharpest, best color stars I could, and to bring out the tiny surrounding stars without losing them in background noise.
This image was made from 210x30s of luminance and 50x90s each of red, green, and blue, for a total of 5 hours and 30 minutes.
Image Capture
Image Capture
Since the stars are the subject in this image I used short exposure times to avoide blowing them out and losing detail. Here is the unstretched master luminance. Only a few stars were saturated and they weren't in the core.
In this stretched version we can still see detail in the core, which is good.
Processing in Pixinsight
Processing in Pixinsight
I'm not going to go over every pre-processing and processing step I took in Pixinsight, as you can find those details in my other processing articles. These steps included:
Pre-processing using the Weighted Batch Pre-Processing Script to make master files for each filter.
Combining the red, green, and blue masters into a single color image.
Removing background gradients (uneven brightness) using Graxpert.
Color calibrating the RGB image.
Sharpening the stars using Blur Xterminator.
Stretching and applying noise reduction.
But we will take a closer look at sharpening and stretching globular clusters.
The uneven background that Graxpert removed from the luminance master.
Blur Xterminator
Blur Xterminator
This image is before deconvolution using Blur Xterminator. BXT uses AI to analyze the size and shape of the stars. The stars should appear as pinpoints, but they actually appear as blurry circles in our images, thanks to atmospheric turbulence and the way camera sensors work. BlurXT analyzes the star shapes and attempts to undo some of that blurring.
After BXT (and also after stretchng and noise reduction).
I don't remember the exact setttings, since I'm writing this some time after I processed the image, but they were probalby close to these.
Stretching and Bringing Out Core Detail
Stretching and Bringing Out Core Detail
Here is the image after applying the automatic screen stretch and permantly brightening the image.
There are two good ways to bring out core detail. One is to stretch the image in stages, using masks to prevent the core from brightening too much in each step.
I chose the other way-using PI's High Dynamic Range process to do the job. Again, I don't remember the exact settings I used, but they were similar to these.
I adjusted the number of layers and the type of scaling function until I got the results I wanted. Using a lightness mask is important. Be sure to click "To intensity" when applying this process to a color image.
The Results After Using Pixinsight
The Results After Using Pixinsight
One 30 second luminance image.
210 stacked luminance images after processing.
150 stacked red, green and blue images after processing.
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