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un:siril [2026/01/24 13:41] – [Running the stacking script] shahalun:siril [2026/01/31 00:32] (current) – [1. Data preparation] shahal
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 ===== - Data preparation ===== ===== - Data preparation =====
 +Test OSC data link: https://drive.google.com/drive/folders/1ULlncwRit-lAi5jrdkFx1ytKaImHEuOl?usp=sharing
  
 Generally there are three kinds of calibration files. Darks, Flats and Biases.  Generally there are three kinds of calibration files. Darks, Flats and Biases. 
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 {{:un:siril_home.png?600|}} {{:un:siril_home.png?600|}}
- Select the main project folder that contains all the required subfolders, including:+ 
 +Select the main project folder that contains all the required subfolders, including:
  Calibration frames (bias, darks, flats)  Calibration frames (bias, darks, flats)
  Light frames  Light frames
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 Siril will now begin the calibration, registration, and stacking process automatically. You can monitor the progress in the ''terminal panel'' on the right side of the interface, where each step of the process is displayed in real time. Siril will now begin the calibration, registration, and stacking process automatically. You can monitor the progress in the ''terminal panel'' on the right side of the interface, where each step of the process is displayed in real time.
  
 +{{:un:siril_script_sucess.png?400|}}
 ==== Opening the stacked image ==== ==== Opening the stacked image ====
  
 Once the script has finished running successfully: Once the script has finished running successfully:
  Click the ''Open'' button in the top-left corner.  Click the ''Open'' button in the top-left corner.
- Load the final stacked FITS file into the image viewer.+ Load the final stacked FITS file into the image viewer. Then click on the ''Linear'' button in the bottom. Select ''Auto Stretch'' . You will see the an auto stretched image.
  
 At this point, you will have a single stacked image ready for further processing, such as background extraction and color calibration. At this point, you will have a single stacked image ready for further processing, such as background extraction and color calibration.
  
 +{{ :un:siril_qyxy1kyrry.webp |}}
 ===== - Foreground subtraction (background/true sky extraction) ===== ===== - Foreground subtraction (background/true sky extraction) =====
  
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  ''Samples per line''  ''Samples per line''
  ''Grid tolerance''  ''Grid tolerance''
 +
 +{{:un:siril_background.jpg|}}
  
 When placing or generating sample points, it is very important to ensure that they lie only on the ''background''—that is, the darker regions of the sky. Avoid placing points on: When placing or generating sample points, it is very important to ensure that they lie only on the ''background''—that is, the darker regions of the sky. Avoid placing points on:
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  ''Right-click'' to remove a sample point  ''Right-click'' to remove a sample point
  
-Once the points are correctly placed on the dark sky regions, Siril models the background (foreground gradient) and subtracts it from the image. This process removes sky gradients and results in a much cleaner and more uniform final image.+Manually place the points on the places where you feel like some glow or artifact is present which is not part of the object or sky. 
 + 
 +Once the points are correctly placed on the sky regions, Siril models the background (foreground gradient) and subtracts it from the image. This process removes sky gradients and results in a much cleaner and more uniform final image. 
 + 
 +{{:un:siril_background_done.jpg|}} 
  
 ===== Star position calibration (astrometry) ===== ===== Star position calibration (astrometry) =====
  
 After stacking, the next step is to perform ''star position calibration (astrometry)'', which assigns accurate sky coordinates to the image. In Siril, this process is not fully automatic and requires user input to guide the astrometric solver. After stacking, the next step is to perform ''star position calibration (astrometry)'', which assigns accurate sky coordinates to the image. In Siril, this process is not fully automatic and requires user input to guide the astrometric solver.
 +
 +
 +{{:un:siril_astrometry.png?400|}}
  
 To begin, make sure the stacked image is open in the viewer. Then go to the ''Image Processing'' section and select ''Astrometry''. For the solver to work correctly, you must provide approximate values for the imaging system, specifically the ''focal length'' of the telescope or lens and the ''pixel size'' of the camera. These parameters are required by the Siril solver to estimate the image scale and search for a valid solution. To begin, make sure the stacked image is open in the viewer. Then go to the ''Image Processing'' section and select ''Astrometry''. For the solver to work correctly, you must provide approximate values for the imaging system, specifically the ''focal length'' of the telescope or lens and the ''pixel size'' of the camera. These parameters are required by the Siril solver to estimate the image scale and search for a valid solution.
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 Once these inputs are set, run the astrometric solver. Siril will attempt to match detected stars in the image with stars from an astrometric catalog based on the provided scale and position, and the progress will be shown in the terminal panel. Once these inputs are set, run the astrometric solver. Siril will attempt to match detected stars in the image with stars from an astrometric catalog based on the provided scale and position, and the progress will be shown in the terminal panel.
 +
 +{{:un:siril_astrometry_pane.jpg|}}
  
 If the solver fails to find a solution, several options can be used to improve the chances of success. You can enable ''Force split solving'', which allows Siril to solve the image in smaller sections, or use ''Downsample image'' to reduce the resolution and make star matching easier. For wide-field images, enabling ''Auto crop'' can also help by removing distorted edges that may prevent a successful solution. If the solver fails to find a solution, several options can be used to improve the chances of success. You can enable ''Force split solving'', which allows Siril to solve the image in smaller sections, or use ''Downsample image'' to reduce the resolution and make star matching easier. For wide-field images, enabling ''Auto crop'' can also help by removing distorted edges that may prevent a successful solution.
 +
 +If Siril Solver fails, we have other ways to plate solve the image. One of them is Uploading the photo in ''[[https://nova.astrometry.net/upload|nova.astrometry.net]]''. We will choose the stacked file and upload that. Then we will see a page that will refresh in every 10 seconds until a solution is found. Then We will see a page like the image. From there click on the New Fits Image to download the image. It is the exact same image with the world coordinate systems  solution in its header.
 +
 +{{:un:nova_astro.jpg?|}} 
  
 When the astrometric solution is successful, the image is plate-solved, meaning that each pixel is now associated with precise celestial coordinates. This calibration is required for subsequent steps such as photometric color calibration, image annotation, and scientific measurements. When the astrometric solution is successful, the image is plate-solved, meaning that each pixel is now associated with precise celestial coordinates. This calibration is required for subsequent steps such as photometric color calibration, image annotation, and scientific measurements.
 +
 +After clicking the 3rd and 4th button bsedide the Autostretch button you can see the co ordinate planes, and the object identifiers in the image. 
 +
 +{{:un:siril_astrometric_solution.jpg?|}}
  
 ===== - Spectrophotometric color calibration ===== ===== - Spectrophotometric color calibration =====
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 Once all required parameters are set, run the SPCC process. Siril will fit the observed stellar colors to the cataloged spectrophotometric data and compute correction factors for each color channel.  Once all required parameters are set, run the SPCC process. Siril will fit the observed stellar colors to the cataloged spectrophotometric data and compute correction factors for each color channel. 
 +
 +{{:un:siril_spcc.jpg?|}}
 ===== Stretching ===== ===== Stretching =====
 +{{:un:siril_unstretched.jpg?|}}
  
-==== Histogram stretch ====+**Histogram stretch**
  
 To perform a histogram stretch, open the histogram transformation tool in Siril with the linear, background-subtracted, and color-calibrated image. First, locate the histogram of the image. Most of the data will be concentrated near the left side. To perform a histogram stretch, open the histogram transformation tool in Siril with the linear, background-subtracted, and color-calibrated image. First, locate the histogram of the image. Most of the data will be concentrated near the left side.
  
-Start by sliding the ''midtone'' slider slightly to the left. This will move the main peak of the linear histogram a little to the right and make it slightly wider. +Start by sliding the ''midtone'' slider slightly to the left. This will move the main peak of the linear histogram a little to the right and make it slightly wider. The ''Midtone'' Slider is the middle one in the bar under the histogram curve. And the left most one is the ''Shadows'' slider.
 Observe how the image brightens and the faint structures become more visible.  Observe how the image brightens and the faint structures become more visible. 
-Repeat this adjustment multiple times, in small increments, gradually moving the midtone slider while monitoring the histogram peak and the image appearance. The goal is to achieve a balance between the highlights and shadows.+Repeat this adjustment multiple times, in small increments, gradually moving the midtone slider while monitoring the histogram peak and the image appearance. The goal is to achieve a balance between the highlights and shadows. 
 Next, adjust the ''black point'' slider carefully. Pulling the black point slider to the right will shift the histogram to the left, increasing contrast. Be careful not to clip data: the leftmost end of the histogram should not cut into significant pixel values.  Next, adjust the ''black point'' slider carefully. Pulling the black point slider to the right will shift the histogram to the left, increasing contrast. Be careful not to clip data: the leftmost end of the histogram should not cut into significant pixel values. 
 Continue alternating between small midtone and black point adjustments until the histogram is widened appropriately, the faint details are visible, and both highlights and shadows are preserved. Continue alternating between small midtone and black point adjustments until the histogram is widened appropriately, the faint details are visible, and both highlights and shadows are preserved.
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 The key is to perform these adjustments gradually and repeatedly rather than making large, aggressive changes in a single step. The key is to perform these adjustments gradually and repeatedly rather than making large, aggressive changes in a single step.
  
-==== Generalized Hyperbolic Stretch (GHS) ====+{{:un:siril_stretch_1.jpg|}}
  
-Once a basic histogram stretch is applied, the Generalized Hyperbolic Stretch (GHS) can be used for finer control:+** Generalized Hyperbolic Stretch (GHS) **
  
-Open the GHS tool in Siril with the stretched image. +Once you have understood the histogram stretch tool, we can use more advance tool like this GHS to have finer control over the stretching. Evn you can use both of the stretching one after another to further refine the image. 
 + 
 +Open the GHS tool in Siril with the unstretched image. 
 Adjust the ''stretch factor'' slightly to enhance faint regions while keeping the bright areas from saturating. Small incremental changes work best. Adjust the ''stretch factor'' slightly to enhance faint regions while keeping the bright areas from saturating. Small incremental changes work best.
 Move the ''symmetry point'' slider slightly to position the stretch curve according to the main data peak. This helps preserve star cores and highlights while brightening the faint structures. Move the ''symmetry point'' slider slightly to position the stretch curve according to the main data peak. This helps preserve star cores and highlights while brightening the faint structures.
 Monitor the histogram and the image as you adjust. Repeat the adjustments in small steps until you achieve a balanced stretch where faint details are visible and bright areas are not clipped. Monitor the histogram and the image as you adjust. Repeat the adjustments in small steps until you achieve a balanced stretch where faint details are visible and bright areas are not clipped.
 Avoid extreme settings: do not pull the sliders to the edges, as this will clip the highlights or shadows and degrade image quality. Avoid extreme settings: do not pull the sliders to the edges, as this will clip the highlights or shadows and degrade image quality.
 +
 +{{:un:siril_ghst.jpg|}}
  
  
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 For denoising, there are three options:   For denoising, there are three options:  
-* ''Full'' applies noise reduction to the entire image.   + ''Full'' applies noise reduction to the entire image.   
-* ''Luminance'' applies denoising only to the brightness channel.   + ''Luminance'' applies denoising only to the brightness channel.   
-* ''Both'' applies denoising to both luminance and color channels simultaneously.  + ''Both'' applies denoising to both luminance and color channels simultaneously.   
 +Before Denoise:  
 +{{:un:siril_denoise1.jpg|}} 
 +After Denoise 
 +{{:un:siril_denoise2.jpg|}} 
  
 For sharpening, you can choose:   For sharpening, you can choose:  
-* ''Stellar sharpening'', which targets only the stars, enhancing their crispness.   + ''Stellar sharpening'', which targets only the stars, enhancing their crispness.   
-* ''Full sharpening'', which enhances both stars and non-stellar structures such as nebulae and galaxies.  + ''Full sharpening'', which enhances both stars and non-stellar structures such as nebulae and galaxies. 
 +Before Sharpening:    
 +{{:un:siril_sharp1.jpg|}} 
 +After Sharpening: 
 +{{:un:siril_sharp2.jpg|}}
  
 Cosmic Clarity uses AI models trained on astronomical images to intelligently separate stars from background structures and noise, enhancing fine details while minimizing artifacts for a cleaner and sharper final image. Cosmic Clarity uses AI models trained on astronomical images to intelligently separate stars from background structures and noise, enhancing fine details while minimizing artifacts for a cleaner and sharper final image.
  
un/siril.1769287299.txt.gz · Last modified: by shahal
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