Introduction to modern narrow band filters & Coloring with Narrowband Images using Pixel Math- Livestream

For this meeting we will have two speakers. Gert will talk about narrowband filters, and Kai will talk about Coloring with Narrowband Images using Pixel Math.

Amateur astronomers in light polluted areas like our region in northern California use filters to reduce the effect of light pollution and give better visual and photographic impressions for certain classes of objects. The first part of this presentation will introduce to the audience to what types of light pollution we face and the types of filters that have been developed for various visual and photographic applications. We will introduce the relatively new development of narrow band filters with multiple pass bands and how these filters are used mainly in astrophotography.

Speaker: Gert Gottschalk

Practitioners of astrophotography usually are rigorous, who try to reproduce images that mimic closely to what humans would have seen if they had perfect vision and no atmospheric distortions. With narrowband images, however, it is often acceptable and encouraged to playfully combine the color channels to arrive at compelling artworks that are still based on the physics of star creations and destructions.

The main challenge with narrowband image processing is how vastly different the magnitude of signal we can detect from the different bands, where the black body emission from stars overwhelms the H-alpha ones, which overwhelms the OIII or SII. To arrive at a color-balanced final image that is relatively noise free, but yet can be acquired with a non-professional setup within a reasonable amount of time, many processing techniques were developed. Today, we will focus on using Pixinsight’s powerful and flexible Pixel Math process (along with other supporting modules).

We will first show how to create a color image from a single channel (typically Ha), 2 channels (e.g. HOO) and 3 channels (e.g. SHO or HSO). Followed by how to add narrowband data to RGB images. We will then demonstrate techniques to improve the color and detail using relatively simple Pixel Math expressions. We will finally deep dive into the more exotic pixel math expressions that we sometimes see referenced in others’ works, and try to explain the logic and reason behind them.

Speaker: Kai Yung

See weblink for Zoom instructions