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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.  | 
	 
 
  
  
  
************************ 
  
	
		| 
		 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.    | 
	 
 
  
  
  
  
  
  
  
 
	 
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