Starguide - A Practical Guide to Astro-Photography

PixInsight 
Linear Image Quality Enhancements

Step 3: Deconvolution

updated: 2025-10-26

Purpose

processing, among other things. Convolution can always be calculated, whereas inversion is not always possible because information can be lost during convolution that cannot be recovered. In order to be able to calculate the best possible inverse convolution, computationally intensive algorithms and procedures have been developed.

A simple example is the sharpening of an image. The process of blurring is represented by a convolution. The sharpening of the image, as supported by many image editing programs, then corresponds to a deconvolution.

Input

The integrated linear Master Light frame from the previous step

Output

An image that contains the essential elements and hides distracting edges or gradients

Previous Step

Step 2: Gradient Correction

Alternatives

• GraXpert (within PixInsight)
• GradientCorrection (PixInsight)
• The MARS Project

Next Steps

Step 4: Color Calibration