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Heart Nebula with rnc-color-stretch

https://old.reddit.com/r/AskAstrophotography/comments/17xrkg3/rnc_color_stretch/

Hello Key_Switches

You can review the images in photoshop or acr, or once you have raw conveter output (tiffs), you operating system image browser.

I downloaded your image, and the data are quite strange. My version of davinci was not compiled with the fits reader, so I converted it to a floating point tiff in ImagesPlus. The data values in the tif file have minimum = 1.405491e-08 and maximum= 1.500956e-05.

I'll assume ImagesPlus did a straight conversion with no scaling (other times I've done this conversion that was the case).

The output from ACR should be 16-bit images with a range from 0 to 63535. So why the output of siril us so strange may be because of some settings you applied.

The stacking step should result in an image that has the same brightness and color as an average input image. If not, the stacking program is modifying the data and usually will be mangling color.

I used davinci to scale the 32-bit floating point image from imagesplus to 0 to 1 in the green channel, by dividing the image by 1.500956e-05.

The other problem with your image is that the flat field is way over corrected (dark doughnut in the center, bright toward the corners). This severely limits getting the nebula to separate from the sky background.

I usually start with something like this:

-rootpower 12 -rootpower2 6 -scurve1 -skylevelfactor 0.01

Full command line:

rnc-color-stretch imagename.tif -rootpower 12 -rootpower2 6 -scurve1 -skylevelfactor 0.01 -obase imagename,rs12,6,sc1,slf0.01 -display

I encode the parameters into the filename so when I try different parameters I can look at different images and see what the effects are.

If you data and flat field are very good, usually -rootpower 20 -rootpower2 12 works well. I usually keep rootpower2 about half of rootpower1.

Your data are pretty good regarding SNR and ignoring the flat problem. I used the image produced from the above command to examine the data and stretch more with the curves tool in photoshop. The BIG problem is the histograms have been aligned (in your siril processing or in ACR)!!!! Aligned histograms mean the average color of the image is gray!!! NEVER DO THAT. That means any dominant color has also been suppressed. The average color in this area is red, so aligning the histograms suppresses red, thus suppressing the H-alpha. It is steps like this (histogram equalization) that leads to the myth that stock cameras are not sensitive to H-alpha, and then we see people punching up saturation (e.g. the other poster here) to try and recover some color. Emission nebulae are very colorful, like neon signs, and with proper processing, saturation enhancement is not needed.

I named your image, after converting to 32-bit float tif and scaling to a 0 to 1 scale: heart-nebula-Nov-16-80min-float-0-1.tif

Next I looked at the result from the above -rootpower 12 -rootpower2 stretch and found a dark park of the image near the center. The upper left and lower right coordinates are: 2505 2818 and 2692 2994. (Note photoshop starts counting a 0,0, davinci at 1,1, so add one if you get coordinates from photoshop.)

So next I tried the following stretch

    rnc-color-stretch heart-nebula-Nov-16-80min-float-0-1.tif  \
       -rootpower 20 -rootpower2 12 -scurve1 -skylevelfactor 0.01 \
       -histogrambox1  2505 2818  2692 2994  \
       -obase heart-nebula-Nov-16-80min-rs20,12,sc1,slf0.01,hbx1 -display

(The \ means continue the command on the next line.)

Result from the above command (reduced to 1500 pixels wide):

I cropped out the center and stretched with the curves tool to make this image (note the beautiful star colors).

The above strtetched images shows a couple of things. First, the heat is there and the SNR is reasonable. With avouding the histogram eqiualization, it will surely pop out nicely with better SNR. Second, with the curves tool brightening, star colors were lost. That is the power of a color preserving stretch: less loss of star color.

Note: I assumed sRGB color space. Better to start out of ACR with Adobe RGB or Rec2020, then results would be better.

Last updated November 18, 2023.