The Christmas tree cluster (NGC2264) and associated nebulosity with duo-band filters

Using an Altair Starwave ASCENT 60ED doublet refractor with field-flattener, a Pegasus FocusCube v2 focuser, an Altair Hypercam 533C 14 bit OSC CMOS camera and a PlayerOne Phoenix 2" filter wheel all mounted on a Celestron AVX mount.  An SVBONY SV165 guide-scope fitted with a QHY-5II-M guide camera was mounted on the imaging scope. An INDI server was running on a Linux computer indoors. The guide camera was connected by USB to another Linux computer indoors running PHD2 autoguiding software via the INDI server. The mount and the focuser were controlled by AstroDMx Capture via the INDI server.

One hour's worth of 5 minute exposures of NGC2264 through an Altair HaO3 filter and one hour's worth of 5 minute exposures through an Altair S2O3 filter were captured by AstroDMx Capture running on an Ubuntu mini computer. 

The Data were debayered and stacked in PixInsight, part processed in PixInsight, Gimp3 and SetiAstroSuitePro. The Ha, S2 and O3 channels were separated out from the HaO3 and S2O3 images and used to contruct narrowband palettes. Siril was used for pixelmath procedures.

The Christmas tree cluster (NGC2264) and associated nebulosity

Hubble palette

Classical SHO

HOS (Canada, France, Hawaii telescope palette: CFHT)

OSH

Pixelmath generated palettes

Gendler palette

ForaaX palette

Again, the PlayerOne Phoenix 2" filter wheel was controlled natively by AstroDMx Capture and proved very useful for rapid filter change of the parfocal Altair 2" duo-band filters filters.

The Seagull and Rosette nebulae with Altair duo-band filters

The equipment used was an Altair Starwave ASCENT 60ED doublet refractor with field-flattener, a Pegasus FocusCube v2 focuser, an Altair Hypercam 533C 14 bit OSC CMOS camera and a PlayerOne Phoenix 2" filter wheel all mounted on a Celestron AVX GOTO mount. An SVBONY SV165 guide scope with a natively connected QHY-5II-M guide camera was used for PHD2 multistar pulse auto-guiding via an INDI server. The mount, and focuser were controlled by AstroDMx Capture via the INDI server and the Altair Hypercam 533C and the PlayerOne Phoenix 2" filter wheel were controlled natively.

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The Equipment

Altair dual-band 2" S2O3 and HaO3 filters were used.

AstroDMx Capture running on an Ubuntu mini computer was used to capture 5-minute exposures through each filter of the Rosette nebula and C50 the Harp cluster as well as of the Seagull nebula IC2177. A total of 1hour 30minutes worth of data: 45 minutes through each filter were captured of each nebula.

Pixinsight was used to stack and calibrate the data. The data were further processed in PixInsight, GraXpert, SetiAstroSuitePro and Gimp3. The Ha, S2 and O3 channels were separated out from the HaO3 and S2O3 images and used to contruct narrowband palettes. Siril was used for pixelmath procedures.

The Seagull nebula IC2177

Hubble palette

HOS (Canada, France, Hawaii telescope palette: CFHT)

OSH

Pixelmath generated palettes

Gendler palette

ForaaX palette

The Rosette nebula and C50 the Harp cluster

Hubble palette

(Canada, France, Hawaii telescope palette: CFHT)

OSH

Pixelmath generated palettes

Gendler palette

ForaaX palette

The PlayerOne Phoenix 2" filter wheel was controlled natively by AstroDMx Capture and proved very useful for rapid filter change of the parfocal Altair 2" filters.

AstroPicsLab image processing software

Every so often I come across a piece of image processing software that I find meets its aims very well. Such a program is the freeware/donationware AstroPicsLab from Italy.

David Regordosa the developer of AstroPicsLab combines the two disciplines, of Artificial Intelligence (AI) and Astronomy.

AstroPics Lab is an AI-powered tool designed to enhance amateur astrophotography.

AstroPics Lab (AL) aims to make it easy anyone who starts in the field of astrophotography to do some image processing.

AstroPics Lab doesn't claim or want to compete with the fantastic tools that already exist, it simply aims to make the work easier for those amateurs who do not have the time and money to process astronomical images with current tools.

The project is called (AL) (AstroPics Lab) in honor of the late physicist and meteorologist Albert Borras, director of the Pujalt Observatory for 16 years, co-founder of Astroanoia and Anoiameteo and science communicator.

AStroPicsLab can:

Remove noise, enhance objects, remove/reduce stars, apply colour automatically, upscale 2x image, intelligent crop, autostretch, luminance layers, change palette, modify colours, 3d effects, enhance stars, etc.

One of the key functionalities is a neural network trained on over 35000 images to remove a wide range of noise types (Gaussian, thermal, cosmic rays, salt‑and‑pepper, etc.) by processing 256 × 256-pixel blocks and reconstructing a clean, detailed result.

The image is divided into small blocks, on which the AI ​​model is applied to reduce noise. Finally, the blocks are put back together to create a final image without noise.

Also a Star Removal Model – Allows users to reduce or remove stars in images.

We shall illustrate the program by processing a high quality JPG image of the Iris nebula captured and stacked in a Seestar S50. It can also work on 16 bit files, PNG, FITS and TIFF. We are using the high quality JPG in this instance as this fits with the philosophy of the software and could make things easier for some Seestar users who don't want to go into stacking subframes in other software. Of course the program is equally well suited to working with stacked images from other imaging systems.

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AstroPicsLab has a variety of functions and processes which can be seen in this short animation.

Alternatively there is a completely automatic processing mode where the user can decide what will be included in the automatic workflow.

The Automatically enhanced image

If the Change View button is clicked the starless image is shown.

Or the Stars image is shown.

Any of the images can be saved.

The final result can be saved and if required, x2 upscaled before saving.

Animation of the before and after automatic processing of the Iris nebula

AstroPicsLab is a valuable addition to the arsenal of tools an astrophotographer can use to process her/his images.

The software can be downloaded from https://astropicslab.com/

Feature release of AstroDMx Capture Version: 2.16.2 (All Platforms)

Nicola has released a new version of AstroDMx Capture

For Linux x86-64 • Linux ARM • macOS x-86 • Apple silicon • Windows 

Mutatis mutandis

1. Added: PlayerOne filter wheel support
2. Added: ZWO camera support (Apple Silicon)
3. Added: ZWO filter wheel support (Apple Silicon)
4. Added: Atik camera support (Apple Silicon)
5. Improved: Cooler readout
6. Improved: QHY TEC cooler controls
7. Improved: Debugging support
8. Updated: QHY SDK
9. Updated: Atik SDK
10. Updated: Altair SDK
11. Updated: Touptek SDK
12. Updated: PlayerOne SDK
13. Updated: ZWO Camera SDK
14. Updated: ZWO Filter Wheel SDK
15. Slew to zenith and stop tracking implemented to facilitate Flat field collection if an illuminated panel is used.

Meanwhile Nicola continues to work on version 3 of AstroDMx Capture making a range of functional and efficiency changes plus new features in addition to making the software Wayland compliant with Qt6.

LuckyStackWorker working on nebulosity

There is a cross-platform tool called 'LuckyStackWorker" for processing stacked solar, lunar and planetary images and also for stacking solar, lunar and planetary images. It runs on Windows, Linux, macOS x86 and Apple Silicon. It is written and maintained by Dutchman Wilko Kasteleijn. It was first released in 2022 and is now on version 7. It requires 16 bit TIFF or PNG images.

For these tests we stacked a Seestar S50 RAW AVI lunar file using the SetiAstroSuitePro Planetary stacker.

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SetiAstroSuitePro Planetary stacker stacking a RAW lunar AVI file from a Seestar S50

LuckyStackWorker processing the stacked image

LuckyStackWorker processing the stacked image

This was LuckyStackWorker doing the job for which it was intended. The test that we did was to use it to sharpen a starless deep Sky image. The image was a starless blend of RGB and SHO data from a QHY Minicam8 and a William Optics 81mm APO refractor, captured by AstroDMx Capture.

We are not claiming that this is an optimal sharpening of the nebulosity because there are numerous controls and settings in the software. This is a demonstration of the possibility that LuckyStackWorker can also be used to sharpen 16 bit starless nebulosity.

Screenshot animation showing the sharpening of the M42/43 nebulosity as some settings are changed

Animation showing the original and the sharpened images of the M42/43 nebulosity

It seems that LuckyStackWorker also has a place in deep sky image processing as well as lunar, solar and planetary imaging.

Producing 'RGB' stars from Ha, O3 and S2 data

When we are doing narrowband imaging we frequently don’t have time to do separate RGB imaging for the stars. This is due to a number of reasons:

The fact that clear nights are so infrequent.

At our imaging place there is only a relatively short window of opportunity to capture narrowband data on any target before it runs into obstructions.

As our imaging is exclusively for the testing of Nicola’s capture software AstroDMx Capture, it is in the best interests of our imaging to capture as much data as possible through each narrowband filter.

Thus the fact remains that we frequently have to use less than ideal stars in terms of their colours. Frequently we have used HOO data to obtain a stars image and then gently adjusted hue and saturation to produce subtle star colours that are usable in the final images.

There are, however  pixelmath based procedures that produces more realistic star colours.

Some pixelmath formulae are:

Method 1

R = Ha * 0.8 + SII * 0.2

G = OIII

B = OIII

Method 2

R = 0.4 * Ha + 0.6 * S2

G = 0.4 * O3 + 0.3 * Ha + 0.3 * S2

B = O3

A simpler blend using only Ha and O3 data:

Method 3

R = Ha

G = 0.2 * Ha + 0.8 * O3

B = O3

These methods produce different but acceptable star colours.

It seems logical to combine the three methods into an average pixelmath formula:

Blend of the three methods (Method 4):

R = ((Ha * 0.8 + S2 * 0.2) + (0.4 * Ha + 0.6 * S2) + (Ha)) /3

G = ((O3) + (0.4 * O3 + 0.3 * Ha + 0.3 * S2) + (0.2 * Ha + 0.8 * O3)) / 3

B = ((O3) + (O3) + (O3)) / 3

Which simplifies to:

R = ((Ha * 0.8 + S2 * 0.2) + (0.4 * Ha + 0.6 * S2) + (Ha)) /3

G = ((O3) + (0.4 * O3 + 0.3 * Ha + 0.3 * S2) + (0.2 * Ha + 0.8 * O3)) / 3

B = O3

The data used here are of the Tadpoles nebula IC410, LBN807. Captured by AstroDMx Capture with a QHY Minicam8 through a William Optics 81mm APO refractor with a 0.8 reducer/flattener. The Ha, O3 and S2 data were stacked and part processed in PixInsight. The stars were removed and kept as Ha, O3 and S2 star images. The starless images were processed as described in the previous article to produce the Gendler palette which for the tests here was channel shifted to Gendler-GRB. The stars were then processed in PixInsight with BlurXterminator set to correct only.

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Starless image of the Tadpoles nebula in the Gendler palette RGB

Starless image of the Tadpoles nebula in the Gendler palette channel-shifted to GRB 

Gendler GRB with Method 1 stars

Gendler GRB with Method 2 stars

Gendler GRB with Method 3 stars

Gendler GRB with Method 4 stars (pixelmath average of Methods 1,2 and 3)

Each method produces stars that are subtly different, particularly the redness of the red stars. Methods 1 and 3 produce vivid red stars whereas in Method 2 the red stars are a more yellowy red. The average of methods 1,2 and 3 produces red stars with a more gentle red rather than a deep red.

These are all subjective views of the results which are only an approximation to true RGB stars. However, the methods produce more realistic stars than any narrowband palette does and the stars are processed separately from the nebula. Our personal preference is Method 4 but in the end it is a matter of personal taste. Moreover, the methods presented here are not exhaustive and it is entirely possible that even more realistic star colours could be produced by other means.

Manipulation of narrowband palettes

Although a lot of the work done here could possibly be done in a single application, I find the most comfortable workflow involves the use of a number of programs. Most of the work will be done here in GIMP 3 but pixelmath will be done in Siril. Stacking, de-noising star removal and de-linearising were done in PixInsight.

Creation of a palette from grayscale images captured through Ha, O3 and S2 narrowband filters.

The data used here are of the Tadpoles nebula IC410, LBN807. Captured by AstroDMx Capture with a QHY Minicam8 through a William Optics 81mm APO refractor with a 0.8 reducer/flattener. The Ha, O3 and S2 data were stacked and part processed in PixInsight.

The monochrome stacked images have their stars removed and are de-noised. Then the starless images are stretched with Curves and then Levels in GIMP 3 so that their histograms are similar and have the same means as closely as possible. This gives the images similar ranges of brightness from darkest to lightest,

H-alpha image

O3 image

S2 image

Producing an SHO image by mapping the S2, Ha and O3 images to R, G and B

Assigning monochrome images to RGB channels

Produces the resulting SHO image of the Tadpoles nebula

The stars can be returned by pasting the stars image onto the starless images and select Screen mode. With the pasted layer in focus, Curves can be used to adjust their prominence to the desired degree before flattening the image.

The other seven narrowband palettes: OHS, OSH, HOS, HSO, SOH, HOO and SOO can be made by the same method in GIMP 3.

There is another group of narrowband palettes that are produced by pixelmath and that was done here in Siril. These palettes are the Gendler palette, the ForaaX palette, the Natural Palette and pixelmath variations on these.

The Gendler palette constructed by pixelmath in Siril

The Gendler palette of the Tadpoles nebula RGB rendering

The stars can be added back as before

Because each channel is a complex pixelmath construct, another process called channel shifting is used to contruct  a further five palette renderings from a palette such as the Gendler palette. 

The Gendler palette image is decomposed into its RGB channels as layers

Decomposing to layers

Decomposed image with the three monochrome layers shown at the right hand side of the screen

The RGB channels are re-mapped in a different order to BRG  (channel-shifting)

The RGB image has been channel-shifted to BRG a totally different rendering

By this procedure, it is possible to produce all five of the channel-shifted renderings of the Gendler palette in addition to the original RGB rendering. The stars are Screened into the image as before, and their prominence adjusted with Curves before flattening the image.

Gendler palette BRG rendering

Gendler palette GBR rendering

Gendler palette BGR rendering

Gendler palette RBG rendering

Gendler palette GRB rendering

It is, of course, possible to similarly construct channel-shifted variations of any pixelmath generated palette.

It is no surprise that the six basic narrowband palettes: HOS, OHS, HSO, SHO, SOH and OSH are simply channel-shifted versions of each other, although they are more conveniently constructed by channel combination from the original monochrome Ha, S2 and O3 images.

It is worth exploring the channel-shifted variations of any pixelmath generated palette as they each reveal the structure of the nebulosity in different ways and some may be more aesthetically pleasing than others.