Each master image will have a different inherent brightness level due to the differences in light transmission in the filter. Before combining each image into a single color image, the brightness levels must be in balance. The easiest way to do this is with the PixInsight Linear Fit Process.
Before we can run Linear Fit, we need to determine which image will be our reference, which should be the dimmest.
By using the Statistics process for each of our images, we can quickly identify which image is the dimmest.
Most likely, the Blue, OIII, or SII will be the dimmest.
Note: Many tutorials recommend using the brightest image (HA or Red). However, this approach will scale the dim images to match the brightest image. This will also scale the noise in the dimmer images, resulting in a noisier final image.
The linear fit process is extremely easy and fast. Simply select the reference image (dimmest), and apply it to the other images by dragging the triangle onto them.
Once done, we can see how the Median value within the Statistics process are similar across the images.
With the brightness levels across all images equalized, the next step is to integrate our channels into a single color image with Pixel Math or Channel Combination. The approach you take will be based on whether you are doing lunar or deep sky imaging