Channel integration is exciting because it is where we get our fist glimpse into what the color image will be. There are numerous ways to integrate channels using Channel Combination process or Pixel Math. Depending on my images, I will switch between the two methods, but before this, we must be sure that we equalized the brightness with Linear Fit.

In this example, I will be combining three narrowband images (hydrogen-alpha, Oxygen-III and Sulphur-II)

With channel integration, this is where some artistic liberties start to influence our decisions.

Channel Combination

The channel combination process is extremely easy. You simply select the images for the R, G and B channel.

Channel Combination
Channel Combination

Once complete, you have a color image.

Combined Narrowband Channels
Combined Narrowband Channels

The intense green color is because the HA channel has the strongest signal and overpowers everything else. This can easily be corrected with SCNR.

Pixel Math

The next option for integrating channels is to use Pixel Math. Pixel Math provides more power in that you can specific how the channels are blended and integrated.

Pixel Math - SHO
Pixel Math – SHO
Pixel Math - Custom Blend
Pixel Math – Custom Blend

In both examples, we want to

  • Create new image
  • Set color space to RGB color

The first Pixel Math operation assigns each narrowband image to a channel. This results in the same output as Channel Combination. This approach is often referred as SHO, and is known as the Hubble Palette.

But in the second example, we

  • Red Channel: Blending SII and HA at 50% each
  • Green Channel: Blend HA at 80% and OIII at 20%
  • Blue Channel: OIII at 100%

Based on this sample, it would appear that the custom blend is the better end result. But this is just the first step with channel integration. If we clean up the green with PixInsight SCNR, we get the following:

The approach and color combination blending formulas you use is a personal preference based on what you want to get out of the image.

What’s Next

With the channels integrated, we now must extract the luminance channel to create a synthetic luminance image.