Free as in Free Beer
When amateur astronomers discuss the software that they use to process their image data there is often an 'elephant in the room'; that being the idea expressed by the saying 'you get what you pay for'. The assumption here is that paid-for software is in some way superior to free software and that the free software is somehow a 'poor man's substitute'.
Let's get rid of this elephant before we proceed. 'You get what you pay for' is totally irrelevant to free software. While this saying holds true in many commercial contexts, it is irrelevant when it comes to free software. Let's see why:
Open Source and Collaboration
Free software, particularly open-source software, thrives on collaboration and community contributions. Here are some key aspects:
Community Contributions: Open source projects may benefit from many contributors worldwide who continuously improve the software. This collaborative effort can lead to higher quality software compared to commercial products developed by a limited number of in-house developers.
Peer Review: The open-source model allows peer reviews and audits, ensuring that bugs are quickly identified and resolved. This peer-to-peer scrutiny often results in more secure and reliable software.
Transparency: Open-source code is transparent, allowing users to verify the software's security and functionality themselves, which is often not possible with proprietary software.
Motivation Beyond Profit
The motivation behind creating free software is often driven by goals other than profit. This includes:
Innovation and Experimentation: Developers create free software pushing technological boundaries, experiment with new ideas, and solve specific problems.
Community and Sharing: Many free software projects are built on the principle of sharing knowledge and tools with the community, fostering collective growth and learning.
User Empowerment: Free software often aims to empower users by giving them control over their tools and data, respecting their freedom and privacy.
Quality and Professionalism
Professional Development: Many free software projects are developed by experienced individual professionals and even large organizations. For example, Linux, a widely-used open-source operating system, is maintained by a global community of skilled developers, including contributions from major companies like IBM, Intel, Microsoft and Google.
Reliability and Performance: Free software can be highly reliable and performant. Apache HTTP Server, VLC Media Player, Gimp and Blender are all examples of free software that are trusted and used by millions worldwide.
Advert-ware and mixed-model software
There is a plethora of web-based software that displays adverts. Photopea is one such free to use program that places adverts on the right hand side of the window, essentially out of the way. The software is extremely powerful and can be changed to subscriptionware if the user wishes to remove the adverts and become free from the few restrictions imposed such as background removal can only be done once a day in free mode.
Donationware
Voluntary Contributions: Donationware is a model where users are encouraged to contribute financially to the software's development on a voluntary basis. This allows the software to remain free for all users while providing a way for those who can and want to support the project to do so.
Sustainable Development: Donations can help sustain the development of the software by providing financial support for developers and covering costs such as hosting or additional tools.
Community Support: Users who donate often feel more invested in the project, fostering a stronger sense of community and encouraging ongoing contributions.
Conclusion
The notion that "you get what you pay for" does not apply to free software due to its unique development model, community-driven improvements, and motivations beyond profit. Free software often matches or even surpasses the quality of proprietary counterparts, proving that value and cost are not always directly correlated.
The free software that we are going to use here are:
ASI Studio developed by ZWO the commercial astronomical equipment company. The software suite was produced by ZWO to work with its own imaging systems, but some of the programs in the suite such as ASI DeepStack can be used to register, calibrate and stack RAW images from astronomical cameras and ASI FitsView which can be used to view Fits files.
GraXpert is an open-source astronomical image processing tool developed by Steffen Hirneisen. This software has AI components. It removes gradients and denoises astronomical images. At the time of writing there is an alpha version that can also preform deconvolution. No doubt this will make its way into the stable releases in the future.
Siril is An open-source advanced tool for astronomical image processing and is developed by a team of contributors from the Free Astro community. The project is led by Cyril Richard, who is actively involved in its development.
Gimp is an open-source free image processing program with a huge developer base and which rivals very expensive and well known subscription software. It also has powerful plugins such as G'MIC and Starnet++.
Cosmic Clarity suite is donationware developed by SetiAstro. Its tools that we shall use are AI based sharpening and denoising components.
Although Siril can be used to calibrate and stack data, we are not going to use it for those functions here, instead we are going to use it for Photometric Colour Calibration of our stacked image. ASI DeepStack will be used for calibrating and stacking data because it provides the simplest and fastest way of doing this for monochrome and RAW colour data from astronomical cameras.
The data and equipment
The data used in this article were captured by AstroDMx Capture using two telescope systems, two cameras and two filters.
System 1
William Optics 81 mm ED APO refractor
ZWO Electronic Focuser
Altair magnetic 2" filter holder
Altair quadband filter.
Altair Hypercam 533C 14 bit OSC CMOS camera
SVBONY SV165 Guide scope
QHY-5II-M guide camera
JJC DHS-1 USB Lens Heater Strip x 3 (For imaging scope, guide scope and ZWO electronic focuser)
Multi USB 4 Port Plug Adaptor
5A 12V Power adapters x 3 (For EAF, Cooled CMOS camera and Lens Heater Strips)
Mains extension lead
AVX GOTO mount which was controlled by AstroDMx Capture via an INDI server running on the imaging computer indoors.
An SVBONY SV165 guide scope with a natively connected QHY-5II-M guide camera was used for PHD2 multistar pulse auto-guiding via the INDI server. The auto-guiding was controlled by a separate Linux laptop indoors.
This system was used to collect RAW colour data on NGC7000
System 2
Stella Mira 66 ED APO refractor
ZWO Electronic Focuser
ZWO Electronic Filter wheel
UV/IR Cut filter
SVBONY SV 605MC 14 bit Cooled, monochrome CMOS camera
SVBONY SV165 Guide scope
QHY-5II-M guide camera
MeLE Quieter 2D fanless mini PC running Fedora Linux
TP-Link LS108G 8 Port Gigabit Network Switch
Tenda P200 x 2 Powerline Ethernet adapters
JJC DHS-1 USB Lens Heater Strip x 3 (For imaging scope, guide scope and ZWO electronic focuser)
Multi USB 4 Port Plug Adaptor
5A 12V Power adapters x 3 (For EAF, Cooled CMOS camera and Lens Heater Strips)
Mains extension lead
The small headless MeLE computer is connected via Ethernet to a powerline adapter which is paired with a matching powerline adapter indoors. This link forms a reliable and encrypted Ethernet connection between the powerline adapters and thus allows the small form factor computer to be accessed by its IP address from any computer on the local network.
AstroDMx Capture is run on the capture computer connected to the local network and can access all of the devices in a similar fashion to how they would be if they were connected directly via USB. PHD2 auto-guiding software is run on the guide computer. This constitutes a distributed system.
This system was used to collect monochrome data on M33
With both systems, Lights, Darks, Flats and Bias frames were captured.
5 minute RAW subs were captured for the colour data and 3 minute subs for the monochrome data.
To be absolutely clear; the following is not a prescriptive formula that should be followed. Rather, it is simply an example of the way that free software can be used to develop a workflow for the processing of image data from capture to final image.
NGC7000 with System 1
Software 1: ASIDeepStack
The simplicity of calibrating and stacking with ASI Studio's ASI DeepStack
Launch ASI Studio
Select ASIDeepStack
Notice that there are four tabs: Bias; Flat, Dark and Light
All that is needed is to select a tab, say Flats. Then drag the folder containing the Flats onto the indicated area.
The Flat tab will be populated with the Flats
Exactly the same thing is done with the Bias, Dark and Light tabs, dragging the appropriate folders to the indicated areas in each of the tabs
Clicking on the Play button in the Stack area will initiate the aligning, calibration and stacking of the Lights (image files).
When the process is finished, the stacked image is presented auto-stretched for inspection
Some limited processing can be done here which does not affect the auto-saved stacked Fits and Tiff files.
Clicking on the disk icon at the bottom will save the image as it appears as a high quality JPG. If the Noise Reduction box is checked, a denoising is applied to the image that is saved. However, it should be stressed that the auto-saved Fits and Tiff files are unaffected and are unstretched.
For some, this may be enough and a presentable image that can be shared has been saved.
The JPG saved before additional processing
The JPG saved after the additional processing
Monochrome M33 data
Similarly the monochrome data on M33 were aligned, calibrated and stacked in ASIDeepStack
The high quality JPG saved with only Noise reduction
Further processing with the other free software
This processing will be done here on the 16 bit colour Fits image of NGC7000 that was auto-saved.
Software 2: GraXpert with AI components
16 bit fits image of NGC7000 loaded into GraXpert
The image was stretched the minimum amount so that the effects of the processing could be seen.
Background extracted
AI Denoised
The stretched, denoised image with linked channels
The stretched, denoised image with unlinked channels
In this workflow GraXpert stretched images with or without linked channels will not be used; however, they do afford other ways of proceeding with the processing.
The Processed (but not the stretched) image was saved as a 16 bit Tiff file.
Software 3: Siril
The processed image from GraXpert was loaded into Siril and Autostretch was turned on so that the image would be visible. (This does not affect the image itself, only its visualisation)
In Image Processing, Photometric Colour Calibration was selected. The object name (NGC 7000) was entered and told to find in the database. When this is done, the required information on the object populates the appropriate fields in the dialogue. Force plate solving and flip image if required were also selected.
Then OK was selected and the image was Photometrically Colour Corrected.
The image was then saved with a new name as a 16 bit Tiff file
Software 4: The Gimp 2.10 including the Starnet++ star-removing plugin.
The image was duplicated and the Starnet++ used to remove the stars after the image was converted from Perceptual gamma to Linear.
Stars removed from a duplicate of the image, and the image flattened.
Starless image pasted as a new layer onto the original starry image and subtracted, producing an image of the stars, and the image flattened.
The starless image stretched with Curves
The stretched, starless image
While still in the Gimp, the image was converted from Linear to Perceptual gamma.
Software 5: Seti Astro's Cosmic clarity AI programs
The stretched, starless image was copied into the input folder of Cosmic Clarity
The Non-Stellar sharpening selected.
Non-Stellar Sharpening PSF left at default.
Non-Stellar Sharpening Amount set to a modest 0.65
The sharpening process in progress
The sharpened image is in the output folder of Cosmic Clarity.
The Cosmic Clarity sharpened image
A more dramatic sharpening could have been achieved by using a higher value for Non-Stellar Sharpening Amount
Back in the Gimp, the stars were replaced by pasting the stars image onto the sharpened, starless image with a combining mode of Addition (although it could have been Screen). Before the image was flattened, the saturation of the stars layer was adjusted with Hue and Saturation, and the contribution of the stars to the image was controlled by Curves. Then the image was flattened, scaled and re-oriented to a more familiar view
The final image of NGC 7000, The North America Nebula
We have shown here that Free Software (in the sense of no cost to the user) can be used successfully and flexibly to process deep sky astronomical images from capture to final image.
