This post describes a simple, robust, and repeatable workflow for processing astronomical images in Siril from an OSC (one-shot color) camera.

It is not an advanced or optimized workflow. It is a workflow designed for:

  • those who are just starting out
  • those who want consistent results
  • those who want to learn how to control noise, rather than trying to correct it at the end

This workflow assumes that Siril is already correctly installed and configured. If you haven't done so yet, start with the previous post on installing and configuring Siril.

By following the steps in order and taking your time, you can obtain balanced images with a controlled background and credible colors.

1 — Prepare the working folder

Create a main work folder and, inside it, the following subfolders:

  • lights
  • darks
  • flats
  • biases

If the files already exist on another disk or in another location, use symlinks instead of copying the data. You avoid duplication, save space, and keep everything organized.

A clean structure prevents errors and facilitates all processing.

2 — Choose the working folder in Siril

Open Siril and select the main working folder you created:

3 — Preprocessing and stacking (automatic)

Run the preprocessing script:

  • Scripts → Siril script files → OSC_Preprocessing

This step automatically handles:

  • calibration (darks, flats, and bias)
  • image alignment
  • final stacking

If you do not have all calibration frames

Choose the most appropriate script:

  • OSC_Preprocessing_WithoutDark
  • OSC_Preprocessing_WithoutFlat
  • OSC_Preprocessing _WithoutDBF

Important note: less calibration means more noise. This is not a limitation of Siril, it is a physical consequence of the data.

4 — Open the resulting image

Open the file created by the script - Open → result_xxxx.fit

The "xxxx" is the total number of seconds of exposure.

The image will appear dark, lacking contrast, and uninteresting. This is normal. At this point, the image is still linear.

5 — Display mode: Stretch (visualization)

Change the display mode to AutoStretch (1).

If the image has very strong color casts, use Unlink channels (2).

This stretch is only visual. It does not change the image data.

 

6 — Crop

Draw a rectangle over the image to exclude irregular edges or areas with incomplete stacking. Anything outside this area only adds noise and makes the following steps more difficult.

 You can drag the sides to adjust or click outside the rectangle to start over.

Right-click to bring up the rectangle – Crop – Crop.

7 — Plate solving (astrometry)

Run the plate solver:

  • Tools → Astrometry → Image Plate Solver

Use the "Get metadata from image" button (1). If the data is filled in, just click "OK." If not, search for the DSO in question (2).

 

This step is essential for modern color calibration (SPCC).

 

If it fails, solve the problem now; do not proceed without this working.

 

8 — Background Extraction

 

Image Processing → Background Extraction

Click on Generate

Remove samples placed over stars or nebulae (right button)

Add samples in clean background areas (left button)

Click Compute Background, readjust the samples, and repeat

When you are satisfied, click Apply

 

Use few, well-placed samples. A poorly done BGE creates more problems than it solves.

9 — Color calibration (SPCC)

Calibrate the image color:

  • Image Processing → Color Calibration → SPCC
  • Choose the sensor and filter used

If plate solving was successful, this step is straightforward.

Completely unrealistic colors indicate problems in previous steps

10 — Return to linear

Change the display mode again:

  • Display Mode → Linear

From here on, all changes will modify the image data.

11 — Stretching (where noise becomes visible)

Noise does not appear in this step — it was already present in the data. Stretching simply makes it visible.

Fundamental rule

Image Processing – Stretches – Asinh Transformation

  • Slowly move the Stretch Factor to the right until you begin to see the main object
  • The purpose of this step is to shift the histogram to the center, making the next step easier

Image Processing – Stretches – Histogram Transformation

  • First adjust the black point, without sticking to the signal
  • Adjust the midtones very slowly
  • Click Apply and repeat the process until the black point is almost stuck to the signal.
  • If you don't like something after clicking Apply, you can undo it, including several steps, and repeat the process.

Avoid large movements. Small cumulative adjustments give better results.

 

The more aggressive the stretch, the more noise you will see.

Image Processing – Stretches – Curves Transformation

  • By clicking on the diagonal line, you add control points. Create one point near the bottom and another near the center. Pull the bottom point slightly down and the top point slightly up. Observe the result. Apply smooth adjustments to the curve, in an S shape.
  • Avoid excessive slopes

It is preferable to take several small steps rather than a single aggressive stretch.

13 — Final touches

Make only minor adjustments:

  • If the image has a green tint, select Image Processing – Remove Green Noise and click Apply
  • contrast
  • moderate saturation
  • subtle color corrections

If you feel the need for heavy corrections, the problem lies in previous steps of the workflow.

14 — Save the image

Save the final result:

  • TIFF for external editing (Photoshop, GIMP, etc.)
  • JPEG for publication

Always save an intermediate version. You will want to go back later.

Key idea for beginners

A good image is not the most stretched one.

It's the one that maintains a clean signal, controlled background, and credible colors, even if that means leaving some weak details unshown.

When you feel like you're fighting noise, you're probably asking more of the image than the data actually allows.