Recent Articles in PixInsight Horizons

Why are images not included in ImageIntegration?? This section is on the interpretation of images outputted from the NormalizeScaleGradent script. This video comes from a question asked on the forum at AdamBlockStudios.com . 

This is an impromptu session to describe a few issues and solutions in a current processing project. This is a unique window into real processing issues found only at AdamBlockStudios.

Masked stretch comes with some tell-tale artifacts that easy to see in final images. Compensating for these artifacts is an area of interest and a simple example is shown in this section.

Depending on the situation, there are many ways to fix issues without resorting to the clone stamp tool. This lesson demonstrates how "Adam Block" would approach the problem and show the solution. 

This is a simplified version of my technique that takes advantage of the Starnet process. I still recommend watching the original version/video... it has more flexibility and instructional value- but this is more utilitarian. 

In this lesson Adam shows a technique that helps reduce star halos when blending images with StarNet. Both Adam's blending and artifact suppression techniques are unique in the wider circles of known ways to approach these tasks- AdamBlockStudios shows you the best stuff first!

In this lesson I demonstrate one way to combine old and new data that are relatively similar to one another. If nothing else works, this might be a way to incrementally improve the integration of the data. Selective rejection is also shown here. 

Download wonderful Data on the Carina Nebula!

This lesson simply walks through using Drizzle on undersampled data. The data is also made available to for practice purposes (and to make a beautiful image of the Carina Nebula). 

In this section we wrap up the processing by looking at one of the few reference images of this object taken using a large professional telescope. We also reiterate the three main elements of this image that needed (by Adam's estimation) to be worked on and ending with an image that hopeful standing in for a QED. (Quod erat demonstrandum... that which was to be shown)

And the big reveal! A combination of FHH (a contrast enhancement script) and Blend (another script) are used to create the nearly final image. Those two choices put together are likely not currently being reproduced by any other astrophotographers! Be one of the first to adopt another power processing tool- found here at AdamBlockStudios!

Finally we are getting to the good stuff. A decision was made to employ the big contrast adjustment on a starless image. Starnet++ was used at this step with a few tweaks. 

This section applies necessary noise reduction to the image in preparation for further strong contrast enhancements. A combination of TGVDenoise as well as MLT are used. 

Here we use a technique of Selective Hue Shift to correct for the excess blue we (that is I) put into the reddish elements of the nebula. This is a important and fundamental technique to know- although here only a subtle application of it is used.

The blue channel is adjusted in such a way that blue structures of GUM 15 are enhanced. MLT, MMT, and an appropriate star mask all make an appearance. 

I consider this an important lesson! I made a common error which I suspect is very easy to do and might be a stumbling point for others. So I show the problem and the solution. This highlights the basic ideas behind ChannelCombination, LRGBCombination and ChannelExtraction. 

An incremental improvement is made through deconvolution of the luminance. Consideration of what kind of luminance is discussed and ultimately it is extracted from the RGB image due to equal weighting given by virtue of the PCC defined channel weights.

We begin by looking at the initial RGB image and considering our artistic directions we might want to follow. Then, as a first step in that direction, DBE is used to mitigate some of the non-uniform illumination (which might harm attempts to increase contrast.)

In this section we learn how to adjust MUREDenoise to give us reasonable results, even if the parameters are not quite right. Then we also determine the best method for using PCC (background neutralization) when the field is filled with colored nebulosity.