What does deconvolution do PixInsight?

What does deconvolution do PixInsight?

Deconvolution is a mathematical operation that can be applied to in effect undo some of this distortion, by first modelling it with some stars in the image. This tutorial aims to discuss two main processes used for sharpening fine details in an image using PixInsight.

What is PixInsight?

Briefly, PixInsight is an advanced image processing software platform. It has been designed specifically for astrophotography and other technical imaging fields.

What is deconvolution image processing?

Deconvolution is a computationally intensive image processing technique that is being increasingly utilized for improving the contrast and resolution of digital images captured in the microscope. A series of images are recorded of the sample, each shifted slightly from one another along the z-axis.

How do you get rid of star halos PixInsight?

TUTORIAL: How to eliminate star halos in PixInsight

  1. Get the left, right, top, and bottom values of the halo.
  2. Clone the image and tell PixelMath to generate a mask from the clone.
  3. Blur the mask.
  4. Apply the mask to our original image, and use HistogramTransformation to remove the halo.

How do you do linear fit on PixInsight?

To apply LinearFit, simply click the small button to the right of the text box for Reference image, select your chosen reference image from the list, click OK and then Apply the LinearFit process to all your open images except the reference image (as PixInsight will complain!).

How does noise reduction work in pixinsight?

There are two primary phases of image processing in PixInsight where noise reduction can occur: linear and non-linear. Within the non-linear phase, there are two primary stages where you may wish to reduce noise, for different fundamental reasons: during stretching, and as part of final processing.

How to reduce the noise of a non-linear image?

Similar can be said about MultiscaleLinearTransform at times. Either of these two processes could be used to reduce noise in the image’s linear state and then apply ACDNR a little to the image once non-linear.

What is signal to noise ratio and why is it important?

We work with images of minimal signal to noise ratio, a ratio that for best results must be increased, often by a significant amount, in order to produce a quality image. Ironically, given it’s importance, noise reduction is one of the most misunderstood, and possibly one of the least understood, aspects of image processing.

What is the pixinsight tool for NR?

This is an NR tool that the PixInsight engineers added some time ago, but which no one quite seems to have figured out how to use. I’ve found it can be a very effective, and naturally adaptive, tool for your final pass of NR over an image after it has been stretched and processed.