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The Problem With PixInsight Color Balance

This tutorial shows how PixInsight's default, 32-bit floating-point, data normalization can upset color balance and how to prevent it.

The following only occurs when PixInsight (PI) loads 32-bit floating-point data created with other programs.

When PI loads seperate R, G and B channels, the data are set to a range of 0.0 to 1.0. This is usually a minor problem because the darkest area of the image is most often a neutral gray and the brightest is a star saturated to white.

So let us consider an image that is not this case. Although Image 1 is an extreme example, it will demonstrate the "potential" for disastrous results in color balance.



Image 1

In the above image, the darkest areas are a neutral gray. The brightest area is the yellow star at the center. When the separate red, green and blue channels are loaded into PixInsight, the data are scaled equally from 0.0 to 1.0 for each channel. This stretches the blue data incorrectly relative to the other two channels.



Image 2 (CCDStack)

Image 3 (PixInsight)

Images 2 and 3 are unprocessed views. CCDStack did not normalize the files and we can see that the bright yellow star is still yellow. However, PI set each color channel to a range of 0.0 to 1.0. This normalization changed the color of the brightest star to white and the white star, to the lower left, is now bright blue.

The below text was taken from the PI process console. We can see that the initial high value for the blue data is much lower than the other two channels. The normalizing result is also unequal for the green and red channels.


Reading 3 image(s):
Rescaling sample values: [356, 10689] -> [0,1]:

Rescaling sample values: [356, 16381] -> [0,1]:

Rescaling sample values: [356, 24238] -> [0,1]:




Image 4

CCDStack RGB Combine


Image 5

PixInsight RGB Combine

Images 4 and 5 were processed identically. The histogram, for image five, shows how the three color channels were not treated equally by PI. The relationship between all three channels is modified.

By chance, Image 5 provides PixInsight with a means to nearly correct the color. The face-on galaxy is a reasonable white reference. However, this type of correction does not take into account galactic extinction. This results in an image with the galaxy slightly blue. It should be slightly yellow. The galactic extinction data show that the blue is reduced by about 6% and the red is increased by 4%. This final adjustment sets the color close to Image 4.




Image 6

RGB created with CCDStack and saved as a

32-bit floating-point R, G & B FITS for processing in Pixinsight

Image 7

RGB created and processed with PixInsight

In images 6 and 7, the unprocessed background level is a neutral gray of 318.

The maximum unprocessed R, G & B values are 67298, 65309 and 65821.

When PI loaded the three color channels, the normalization set the upper values for the green and blue to match the red. This was about a 3% increase for the green and blue. With equal stretching, we can see that the PI version has less vibrant reds and a loss of low-level color. The histograms show a striking difference.

Because this image has neutral gray background areas, we again have a means to correct the PixInsight color. By setting the black point, for the green and blue, equal to the red, the color is corrected to a close match with image 6.



The Solution

If you use eXcalibrator or G2V color balancing, then you are interested in consistency and reasonable color. You are a follower of the CAFÉ Doctrine... that is Color As From Earth. The above PixInsight normalization can make your Image-train calibration and color balancing efforts pointless.

Image 5 shows the potential for problematic PI color. Without the spiral galaxy, for a white reference, there is no objective way to correct the color. The user will have to guess.

Some astro photographers have the desire to assemble their images only with PI. I feel it is better to use whatever program works best for a particular phase of the process. Here are my suggestions for avoiding the above-stated PI color problems.

Calibrate your images, both color and luminance, with a program that does not normalize the data by default. I use CCDStack. Save the images as 32-bit floating point FITS. By not using PixInsight, the data are saved in their original format, with no stretching.

With the color data, I use CCDStack to register, stack and create the RGB image. This allows accurate use of G2V or eXcalibrator color balancing. I save the RGB image as a 32-bit floating point FITS for loading into PI. You may also use a TIFF format.  When PI loads this image, it does not make any changes to the color.

With luminance data, I register and stack the sub exposures with PI. For greater precision, use the 64-bit option.

Now, with 64-bit luminance and 32-bit color, I can best take advantage of the powerful PixInsight routines.

For final touch up, I still rely on PhotoShop.