Focal Pointe Observatory
Astrophotography by Bob Franke

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How Sub Exposure Normalization Can Affect Color Balance

 

With calibrated red, green and blue sub exposures, taken under ideal conditions, the final RGB image should have good color. In reality, the conditions are never ideal. This is especially true when data are required over multiple nights. The overall intensity of individual exposures will vary. This is why we normalize the data.

Normalizing the sub exposures compensates for variations in sky background and transparency. This allows data rejection routines to better remove outlier pixel values and undesired artifacts. Normalized data produce a better result when the image stack is mean combined.

For proper normalization, it is important to select the best reference image for each color filter. This test shows how changing the reference image can affect the overall color balance. Additionally, the test shows that eXcalibrator will correct the color balance in the case of a poor normalization choice.

In the following "real-world" test, the sub exposures very greatly. The red, green and blue image stacks were normalized with CCDStack. I used CCDStack's Scalar and Offset methods by selecting the background and the core of the galaxy.

For the red and green filters, the image with the brightest galaxy core was used for the reference image. To show the potential for color change, two image stacks were created with the blue data. One stack's reference image was the one with the brightest galaxy core. The other stack used the image with the dimmest galaxy core.   

 

The following "mouse over" image comparison shows how the color balance changes with the different normalization for the two blue filter stacks. The dimmer normalization reference image produced a final RGB result with a yellow bias. Both images used RGB combine ratios of 1,1,1. The two images were processed side-by-side with identical procedures.

 

 

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For the second part of the test, both sets of R, G and B images were first processed with eXcalibrator. The two results are shown below. The first screenshot is with the dimmer blue normalization reference image. The second uses the bright reference image. Note the difference in the circled RGB color correction ratios. To compensate for the dimmer normalization, the value for the blue channel is much higher in the first example.

 

 

 

 

The two RGB images, in the following "mouse over" comparison, were created with CCDStack using the eXcalibrator RGB color correction ratios. The PixInsight processing was done side-by-side with identical functions. Each processing instance was applied by dragging and dropping it onto each image.

The final images look identical and the differences in their histograms are barely visible. This shows that eXcalibrator corrects the color balance for improper normalization choices. A poor choice for the normalization reference image may produce a final image with a reduced signal-to-noise ratio. However, eXcalibrator maintains proper color balance.

 

 

Image Acquisition and Processing Details

RGB  900 min (20 x 15 min. each filter) Bin 2x2

eXcalibrator for color balance calculations.

CCDStack:

Sub exposure calibration, registration, data rejection, mean combining and RGB creation.

PixInsight:

Gradient removal with DynamicBackgroundExtraction, ACDNR for noise reduction, nonlinear stretching with HistogramTransformation and color saturation. Finally, the background was tweaked to a neutral gray by aligning the three color channels with HistogramTransformation.

PhotoShop:

For adding text to the images and saving JPEGs for the web.