H-alpha image colourisation and the adding of to-scale images of the Earth and Jupiter with Sylvain Weiller's 'Solar Gun' software

The monochrome solar H-alpha image showed lots of structure but it had a background gradient as frequently happens. In a colourised image background gradients show up much more than in monochrome images. It is best therefore to reduce or eliminate the background gradient.

Click on an image to get a closer view

The background extraction was carried out in GraXpert

The interpolation method used was Kriging. the sampling points were set automatically and any that overlapped the edge of the Sun were either moved or removed.

Animation alternating between the original image and the Gradient-Corrected image

The background, which was lighter at the bottom of the image is much more even following background extraction.

Gradient-corrected monochrome image of the Sun

The software used to colourise the image and also to add to scale, images of Jupiter and/or the Earth was Solar Gun, written by Sylvain Weiller and can be obtained HERE.

Solar Gun in operation

Colourised image of the H-alpha Sun with added scale images of the Earth and Jupiter

Solar Gun can apply negative colouration

Negative Colourised H-alpha image

Solar Gun is a welcome addition to a Solar-imager's toolkit and produces pleasing results. It should be noted that in addition to the palettes provided by the software, it is possible to extract a palette from almost any other solar image using another of Sylvain's programs: Color Palette Generator, and the generated palette can be used in Solar Gun to colourise your image.

Colourising a Ca K-line image with a palette produced in Color Palette Generator from a Ca K-line image on the Internet

Of course, the placing of to-scale images of Jupiter and or Earth is optional.

Gimp workflow for fixing elongated stars Part 3

 Gimp workflow for fixing elongated stars Part 3

This workflow is possibly the simplest and can be done either in Gimp or Photoshop. It uses the EQ mounted Seestar S50, 2h of 30s exposures that produced an image with slightly elongated stars when stacked. The elongation of the stars was in one direction.

The flowchart shows the workflow of Part 3

Click on an image to get a closer view

Flowchart

Original Image with elongated stars

Image with original nebula and repaired stars

Animation of Original Image with elongated stars and Image with original nebula and repaired stars

This seems to be a reasonable workflow for fixing stars that are elongated in one direction.

Gimp workflow for fixing elongated stars Part 2

Gimp workflow for fixing elongated stars Part 2

Click on an image to get a closer view if required.

We shall use the same EQ mounted Seestar S50 data that we used in Part 1.

In Part 1 we saw that elongated stars were distorted back into shape by using Select by Colour, Select > Grow and the Distort filter Value Propagate.

The Value Propagate Distort filter propagates the edges of pixels in various controllable directions as shown by the Value Propagate dialog. This distorts the various objects in the image without changing the size of the image.

More White Propagate

More Black Propagate

It can be seen in these dialogs what is propagated and in what direction.

Gimp workflow Part 2

This workflow is simpler in some ways than the workflow in Part 1.

However we do not select the stars, we work on the entire image.

Part 2 workflow

   Load the image with elongated stars into Gimp (It is best if the image is a 16 bit linear image. It can       be converted in Gimp if required). (Duplicate it because it will be required later.)

   Apply Filters > Distorts > Value Propagate to the image more than once, alternately using More White and More black controlling the direction(s) of propagation each time and finishing with More black. (Probably 2 or 3 applications of Value Propagate will be enough to distort the stars into the correct shapes). Even 1 application of Value Propagate might make the stars round. Later, when the stars are removed they can be added back with less prominence to compensate for their increased brightness.

    Of course everything in the image will have been slightly distorted but that doesn't matter

    Remove the stars from the original image using Starnet++

Here we are going to use the command-line version of Starnet++ but using a small Python program and an IDE called Thonny to control it and make its use simpler.

We have tested this in Windows and in Linux and they both work identically and perfectly.

First it is necessary to download and extract the Starnet++ command line software for either Windows or Linux as required. We have extracted it to the Desktop in both cases. You do the same, you can always put it somewhere else at a later date if required.

It can be downloaded from https://www.starnetastro.com/download/

Then it is necessary to download the Python IDE Thonny for the appropriate operating system.

Follow the download link from https://thonny.org/  download and install Thonny.

Copy the following script into a text editor and save it as Starnet-plus-plus.py into the Starnet++ folder on your desktop

import subprocess

# Ask user for the input filename

input_file = input("Enter the input image filename (must be a 16-bit TIF without an alpha channel): ")

# Ask user for the output filename

output_file = input("Enter the Output image filename: ")

# Run StarNet++ command

subprocess.run(["./starnet++", input_file, output_file])

print(f"Processing complete. Output saved as {output_file}.")

There are some test data that you can practice on in the Starnet++ folder on your desktop this folder. This is where your 16 bit .tiff image to have its stars removed needs to be placed. It is also where the resulting starless image will be placed. In this example we placed our 16 bit .tiff image. Open the Starnet++ folder and right-click on Starnet-plus-plus.py and select Open With Thonny.

This will launch the Thonny IDE with Starnet-plus-plus.py open in it.

Linux Version

Windows Version

The Linux and the Windows version look essentially the same and they both have the green triangle RUN button at the top of the Thonny window.

Clicking on the Run button will run the program and the user is asked to enter the 16 bit .tiff filename (the file must already have been placed in the Starnet++ folder)

When the input filename has been entered and Enter has been pressed the user is asked to enter the filename required for the starless image. Any filename such as starless.tiff could be used.

As in 3) above, pass into the program the Original image with the elongated stars, which will have the stars removed and just contain the original nebula.

Start of the Thonny run

Finish of the Thonny run

The starless original image processed to the user's requirements Image A

Distorting the original starry image to correct the stars

Part of the original starry image with elongated stars

First Value Propagate Distort

Second Value Propagate Distort

Preparing stars to add back to the starless image. 

Remember that the stars that were removed from the original image were elongated.

Image with stars fixed (Image B)

Image B with stars removed (Image C)

Image C subtracted from Image B as layers and flattened, producing an image of the stars (Image D)

Image D is then added as a layer to Image A and flattened, producing an image with the original nebulosity and the repaired stars. Before the image was flattened and Image D was the top layer, curves was applied to the top layer to slightly reduce the prominence of the stars in the final image.

Final image of M16 

The stars have been considerably improved by this process and we are satisfied with the result.

We have used a Python program running in a Thonny IDE as an adjunct to the Starnet++ command-line program to make the use of it simpler. However, of course, depending on the environment in which you are working, Starnet++ could have been used as a Gimp plugin (but not for Gimp 3 at the time of writing) or as a Siril plugin. It is my practice to use discrete programs to do discrete processes such as GraXpert to extract backgrounds and denoise and Siril to photometrically correct images. In this way, the command line Starnet++ fitted in well.

Gimp workflow for fixing elongated stars Part 1

Gimp workflow for fixing elongated stars Part 1

Click on any image to get a closer view

Our first attempt at EQ mode Seestar S50 30s exposures was on M16 the Eagle nebula.

The Seestar EQ mounted using a Skywatcher EQ wedge

120 x 30s exposures were captured that is a total exposure time of 1 hour. Tracking wasn’t particularly good, with many of the individual sub-frames showing some slight star trailing which was not severe enough to cause the frame to be rejected during capture.

The sub-frames were pre-processed and stacked using the Siril Script: Seestar_Preprosessing.ssf

The resulting stacked image shows a number of typical problems. There is a gradient across the image, there are some edge artefacts just visible due to the imperfect tracking and also slightly elongated stars. The image shown here is stretched for viewing but is still linear.

Detail from the image above showing the distorted stars

It can be seen clearly that the stars are trailed slightly in a roughly horizontal direction

The linear image was taken into GraXpert where the background was extracted and the image denoised and the unstretched image was saved as a 32 bit fits image.

This image was then opened in Siril where it was plate solved and then Photometrically Color Corrected. Then the image was cropped to remove the edge stacking artefacts.

The linear image was opened in the Gimp and Colors > Curves were used along with Levels to brighten up the image and keep the dark areas dark.

The slight star trailing distortions are clearly visible.

The next stage is to use a Distort Filter, Value Propagate to fix the stars in two stages.

In the Gimp:

    Tools > Select > By Color Select

     We set the threshold to 100 (but it might depend on the image being processed)

    Click on a star and most of the stars should be selected.

    Click on Select > Grow

*** (see later)

     We set the Grow factor to 3 pixels (but it might depend on the image being processed)

        Click on Filter > Distort > Value Propagate

The Mode is More white (larger value)

The boxes by To left and To right have been unchecked. This results in the stars being brighter but more round.

Click on OK

Click on Select None and we have an image with bigger, rounder stars.

Tools > Select > By Color Select

Click on a star

Click on Select > Grow

 We left the Grow factor at 3 pixels

Click on Filter > Distort > Value Propagate

The Mode is More black (smaller value)

The boxes by To top has been unchecked. This results in the stars being smaller and even more round.

In the Gimp, the Starnet++ plugin is used to remove the stars and to produce a star image.

(The star image is made by subtracting the starless image as an added layer, from the starry image and then flattening the image)

Starless image

Stars image

The stars image is then pasted as a layer onto the starless image. The Mode Addition was used to display the stars in the image.

Then  Colors > Curves was used to reduce the stars to the required amount in the image before the image was flattened. This process can make the stars as conspicuous or inconspicuous as required.

Image with the fixed stars returned at the required amount

Animation of a detail of Elongated stars and Corrected stars

*** It should be noted that when using Select by Colour and Select > Grow, if any of the selection spills out onto areas of the nebula for example where it is not required, those areas can be protected by holding down Ctrl and drawing around the affected area with Free Select, on releasing Ctrl, the area will have been deselected whilst the rest of the stars remain selected

Deselected area

It should be remembered that at the time of writing, Starnet++ has not yet been ported to Gimp 3.0. Therefore Gimp 2.10 had to be used. However, it would have been possible to do the star removal using Starnet++ in Siril, if Gimp 3.0 was to be used for the Value Propagate Distort filter.

This workflow has substantially improved the stars in the image. It should be noted that an AI process has NOT been used to repair the stars. The only places where AI processes are used were in background extraction, de-noising and star removal. Non of these processes produce changes to the structure of the nebulosity and introduce unreal aspects to the image. The changes in size and shape of the stars all takes place in the Value Propagate dialogue.