Tag Archives: PixInsight

PixInsight vs Astro Pixel Processor: Which is Best for Astronomical Image Stacking?

Astrophotographers aiming to produce high-quality deep sky images rely on specialised software to stack and process their images. Two of the most popular choices for astronomical image stacking are PixInsight (PI) and Astro Pixel Processor (APP). While both tools offer powerful capabilities, they cater to different user needs and workflows. In this article, we explore the pros, cons, and key differences between PixInsight and Astro Pixel Processor to help you decide which is best for your astrophotography workflow.

PixInsight: Precision and Advanced Processing

PixInsight has built a reputation as the gold standard for deep sky image processing, offering unparalleled control over stacking, calibration, and post-processing.

Pros of PixInsight:

  1. Highly Customisable Processing – PI provides an extensive suite of tools and scripts that allow users to fine-tune every step of the image stacking and processing pipeline.
  2. Superior Calibration and Integration – The calibration and stacking tools in PI, such as Weighted Batch Preprocessing (WBPP), allow for precise control over light frames, darks, flats, and bias frames.
  3. Advanced Noise Reduction and Detail Enhancement – Features like Multiscale Linear Transform and Deconvolution provide powerful ways to refine details and suppress noise.
  4. Script and Process Automation – Users can automate complex workflows using PixelMath and scripting tools, streamlining repetitive tasks.
  5. Extensive Community Support and Plugins – A vast community of astrophotographers contributes to plugins, scripts, and detailed tutorials.

Cons of PixInsight:

  1. Steep Learning Curve – The interface is not beginner-friendly, requiring significant time and effort to master.
  2. No Native GPU Acceleration – PI relies heavily on CPU power, making processing times longer on large datasets compared to GPU-accelerated software. CUDA based GPUs can be added with the relevant runtime libraries.
  3. Expensive One-Time Purchase – The upfront cost can be high, though it does offer lifetime access without subscription fees.
  4. Recent Performance Issues on Windows (Reported by me) – Some users have reported significant performance issues with PixInsight on Windows 11, particularly with the latest 24H2 update. Discussions on the PixInsight forum indicate that versions 1.8.9-2, 1.8.9-3 and 1.9.2
    exhibit degraded performance on certain high core CPU systems, which only appears to affect the Windows version of PixInsight. Users running high-end hardware may experience lower-than-expected processing speeds until a fix is released.

    https://pixinsight.com/forum/index.php?threads/new-xeon-gen-5-system-low-performance-looks-like-1-8-9-2-3-dont-like-w11-24h2.24249/

Astro Pixel Processor: Simplicity and Efficiency

Astro Pixel Processor (APP) is designed for astrophotographers who want a more streamlined and intuitive approach to stacking and initial image processing.

Pros of Astro Pixel Processor:

  1. User-Friendly Interface – APP provides a more intuitive experience with a structured workflow, making it easier for beginners to get high-quality results.
  2. Automatic Calibration and Stacking – The software simplifies the pre-processing steps, requiring minimal manual intervention.
  3. Multi-Channel and Multi-Session Support – APP excels at handling mosaic projects and multi-filter data, making it ideal for narrowband imaging.
  4. Optimised for Speed – The use of efficient algorithms and multi-threading improves processing times, especially on modern CPUs.
  5. Excellent Gradient Reduction and Light Pollution Removal – The Local Normalisation Correction (LNC) and Adaptive Background Neutralisation (ABN) help correct background gradients effectively.

Cons of Astro Pixel Processor:

  1. Less Advanced Post-Processing – While APP is excellent for stacking, it lacks the sophisticated post-processing tools found in PixInsight.
  2. Subscription-Based Model – Unlike PI, APP requires an annual licence or a higher-cost perpetual licence.
  3. Limited Customisation of Algorithms – Users have less control over individual processing parameters compared to PixInsight.

Key Differences Between PixInsight and Astro Pixel Processor

FeaturePixInsight (PI)Astro Pixel Processor (APP)
Ease of UseSteep learning curve, complex UIUser-friendly and intuitive
Stacking PowerAdvanced, fine-tuned stackingFast, automated stacking
Calibration ToolsExtensive and manual controlAutomated and efficient
Post-ProcessingIndustry-leading, full-featuredBasic adjustments available
SpeedCPU-based, can be slow, recent Windows issues reportedFaster due to optimised threading
PricingOne-time purchase (£200+)Subscription or perpetual licence (£100+/year)

Which One Should You Choose?

  • If you want maximum control, professional-level processing, and a comprehensive astrophotography workflow, PixInsight is the superior choice.
  • If you prioritise ease of use, efficient stacking, and automation while still achieving excellent results, Astro Pixel Processor is a great alternative.

Many astrophotographers use both (Like me)—APP for stacking and initial processing, followed by PI for detailed refinement and final adjustments.

Regardless of your choice, both PixInsight and Astro Pixel Processor are powerful tools that can elevate your astrophotography, helping you extract the best possible detail from your hard-earned data.

Creating a Hubble Palette Image from OSC Dual Band Data

Many people like myself have transitioned from a MONO camera to a One Shot Colour (OSC) for whatever reason, for me it was all about not being able to get the required amount of time due to weather conditions here in the UK. When I first considered moving to an OSC camera, it dawned on me that I would not be able to produce the vibrant Hubble Palette images that I could produce by imaging with specific filters on my MONO camera, specifically Hydrogen Alpha (Ha), Oxygen 3 (OIII) and Sulphur Dioxide 2 (SII) which would then be mapped to the appropriate colour channels when creating the final image stack.

Now along came Dual and Tri band narrowband filters for OSC cameras which peaked my attention, the Dual Band filters allow Ha and OIII data to pass, the Tri Band filters allow Ha, Hb (Hydrogen Beta) and OIII to pass but at a high Nm value. I reached out to my friends at Optolong who had two filters, the L-eNhance and the L-eXtreme, the L-eNhance is a Tri Band filter, but after speaking with Optolong it would not work well for me at F2.8, so I went with the L-eXtreme Dual Band filter which has both the Ha and OIII at 7nm.

After receinving my ASI6200MC Pro, I decided to start acquiring data on a 1/2 to 2/3 moonlit nights on the North America Nebula, and so far when writing this post I had acquired a total of 60 frames of 300 seconds each at a gain value of 100, I processed the image my normal way in PixInsight and below is the result of the image:

North America Nebula, 60x300S at Gain100, Darks, Flats and BIAS frames applied with the ASI6200MC Pro using the Optolong L-eXtreme Dual Band 2″ Filter

I thought that my data looks good enough to work with and experiment with trying to build an SHO (Hubble Palette) image with, and I have spoken with Shawn Nielsen on this exact subject a few times so he gave me some hints and tips especially with the blending of the channels. So off I went to try and produce an SHO image.

Before we start, there are some requirements:

  • This tutorial uses PixInsight, I am not sure how you would acomplish this with Photoshop since I have not used PhotoShop for Astro Image Processing for a number of years
  • Data captured with a One Shot Color (OSC) camera using a Dual or Tri Band Narrowband filter
  • Image is non-linear…so fully processed

Step 1 – Split the Channels

In order to re-assign the channels, you have to split the normal image into Red, Green and Blue channels, I found this to work better on a fully processed “Non-Linear” image as above, once this was done, I renamed the images in PixInsight to “Ha” – Red Channel, “OIII” – Blue Channel and “SII” – Green Channel, this makes it easier for Pixelmath in PixInsight to work with the image names. Once this was done, I used PixelMath to create a new image stack with the channels assigned, and this is how PixelMath was configured

Red Channel = SII
Green Channel = 0.8*Ha + 0.2*OIII
Blue Channel = OIII

Once applied this produced the following image stack (do not close the Ha, OIII or SII images, you will need these later on):

SHO Combined image from PixelMath

Step 2 – Reduce Magenta saturation

As you can see from the above image, some of the brighter stars have a magenta hue around them, so to reduce this, I use the ColorMask plugin in PixInsight (You will need to download this), and selected Magenta

ColorMask tool with Magenta selected

When you click on OK, it will create the Magenta Mask which would look something like this:

Once the mask has been applied to the image, I then use Curves Transformation to reduce the saturation which will reduce the Magenta in the image


The result in reducing the magenta can be seen in this image, you will notice there is now no longer a hue around the brighter stars

Result after Magenta Saturation reduced using Magenta ColorMask and Curves Transformation

Step 4 – ColorMask – Green


Again using the Color Mask tool, I want to select the green channel, as we will want to manipulate most of the green here to red, so again ColorMask:

This then produced a mask that looks like the following:

Step 5 – Manipulate the Green Data

Once the Green Mask has been applied to the image, since most of the data in the image is green, we are looking to manipulate that data to turn it golden yellow, so for this we use the Curves Transformation again

The above Curves transformation was applied to the image three times whilst the the green mask was still im place, and this resulted in the following image changes:

Resulting image after green data manipulated in the red channel using Curves Transformation

So as you can see we are starting to see the vibrant colours associated with Hubble Palette images

Step 6 – Create a Starless version of the OIII Data

Now remember I said not to close out the separated channel images, this is because we are going to want ot bring out the blue in the image without affecting the stars, so for this we will turn the OIII image into a starless version by using the StarNet tool in PixInsight

Here’s the OIII Image before we apply StarNet star removal:

Default settings used in the StarNet process

This resulted in the following OIII image with no stars:

Step 7 – Range Selection on OIII Data

Because we do not want to affect the whole image, we will use the range selection tool on the starless OIII image to select areas we wish to manipulate, now we have to be careful that the changes we make are not too “Sharp” that they cause blotchy areas, so within the range selection tool, not only do we change the upper limit to suit the range we want to create the mask for, but we also need to change the fuzziness and smoothness settings to make it more blended, these are the setings I used:


Which resulted in the following range mask

Step 8 – Bring out the Blue with Curves Transformation

We apply the Range Mask to the SHO Image so that we can bring out the Blue in the section of the nebula where the OIII resides, with the range mask applied we will use the Curves Transformation Process again as follows:

Curves transformation process to increase blue, reduce red and increase saturation of image with rangemask applied

The result of which is:

Result after first curves transformation with RangeMask applied

As you can see we have started to bring out the blue data, but we are not quite there yet, with the range mask still applied, we will go again with the curves transformation only this time, just reducing the red element:


The result of the 2nd curves transformation with the Range Mask is as follows:

Resulting image after 2nd pass with Curves Transformation to remove the red elemtn in the range mask

Step 9 – Apply Saturation against a luminance mask

On the above image, we extract out the luminance and apply as a mask to the image, and we then use the Curves Transformation for the final time to boost the saturation to the luminance

Luminance Mask to be applied to image
Curves Transformation with Luminance Mask applied

Final Image

I repeated the same process on my Elephant’s Trunk Nebula that I acquired the data when testing out the ASI2400MC Pro and this was the resulting image:

I hope this tutorial helps in producing your SHO images from your OSC Narrowband images, I know many of my followers have been waiting for me to write this up, so enjoy and share.

NGC 2264 – Cone Nebula and Christmas Tree Cluster in HaRGB

Located in the constellation of Moneceros, this image shows both the Cone Nebula and the Christmas Tree Cluster, located around 2600 light years from earth the Cone Nebula being an emmision Nebula

Image Details:

101x150S in R
101x150S in G
101x150S in B
101x300S in Ha

Total capture time: 21 Hours

Acquisition Dates: Jan. 9, 2019, Jan. 31, 2019, Feb. 3, 2019, Feb. 14, 2019, Feb. 15, 2019, Feb. 23, 2019, Feb. 24, 2019, Feb. 25, 2019, Feb. 26, 2019, Feb. 27, 2019, Feb. 28, 2019, March 24, 2019, March 25, 2019, March 26, 2019, March 28, 2019, March 29, 2019

The NBRGB Script in PixInsight was used to blend the Ha into the RGB Image

101 Darks, Flats and Flat Darks were used in the frame calibration

Equipment Details:
Imaging Camera: Qhyccd 183M Mono ColdMOS Camera at -20C
Imaging Scope: Sky-Watcher Quattro 8″ F4 Imaging Newtonian
Guide Camera: Qhyccd QHY5L-II
Guide Scope: Sky-Watcher Finder Scope
Mount: Sky-Watcher EQ8 Pro
Focuser: Primalucelab ROBO Focuser
Filterwheel: Starlight Xpress Ltd 7x36mm EFW
Filters: Baader Planetarium RGB and Ha
Power and USB Control: Pegasus Astro USB Ultimate Hub Pro
Acquisition Software: Main-Sequence Software Inc. Sequence Generator Pro
Processing Software: PixInsight 1.8.6

M78 / NGC 2068 in RGB

This is the first time I have ever imaged this object, I will re-visit next year when I will image at F2.8 with a wider field of view using a keller reducer.

Since this object is in the southern area of sky, I am limited by trees and the house on the data I can capture in a single night

Image Details:
101x150S – Red
101x150S – Green
101x150S – Blue

101 Darks, Flats and Dark Flats

Image Acquisition Dates: Jan. 1, 2019, Jan. 2, 2019, Jan. 8, 2019, Jan. 9, 2019, Jan. 27, 2019, Jan. 28, 2019, Jan. 30, 2019, Feb. 10, 2019, Feb. 20, 2019, Feb. 23, 2019, Feb. 24, 2019, Feb. 25, 2019

Equipment Used:
Imaging Camera: Qhyccd 183M Mono ColdMOS Camera at -20C
Imaging Scope: Sky-Watcher Quattro 8″ F4 Imaging Newtonian
Guide Camera: Qhyccd QHY5L-II
Guide Scope: Sky-Watcher Finder Scope
Mount: Sky-Watcher EQ8 Pro
Focuser: Primalucelab ROBO Focuser
FIlterwheel: Starlight Xpress Ltd 7x36mm EFW
Filters: Baader Planetarium RGB and Ha
Power and USB Control: Pegasus Astro USB Ultimate Hub Pro
Acquisition Software: Main-Sequence Software Inc. Sequence Generator Pro
Processing Software: PixInsight 1.8.6