Recent Articles in PixInsight

Found here is a collection of scripts that show up at various points (or routinely) in lessons by Adam Block. They are the intellectual efforts of their authors- please do thank them if you find the scripts useful. Click each link to download them. Follow the installation instructions I present in Fundamentals concerning scripts.

This page contains a link to download the entire workflow project for NGC 3486. It therefore contains everything I did to the image. There are very few resources of this type out there!

This video is part of the PI Edition of the Cosmic Canvas. It is available to all PI Horizons members. This is Part 1 of 8 sections which show how to process a very short data set into something (hopefully) attractive. 

The Cosmic Canvas is Adam's "Bob Ross" like delivery of a complete processing session starting from scratch and producing a final rendered image. 

This is a second example of the use of Local Normalization. It is a bit more subtle than the first example and the demonstration deals with attending to smaller scale issues. This second was made as a way to compare the results of selective DBE (placing samples on problem areas) with what Local Normalization does with the same data. 

This lesson shows an excellent example of the use of Local Normalization to correct for non-uniformity of illumination due to various things (in this case high thin clouds). 

This page contains a link to download the process icons for the WorkFlow section of PixInsight Fundamentals. 

You need to be a member to access this file.

Here are the final steps in this fundamental processing workflow. Nose reduction is the key task. This isn't necessarily the end of the adjustments that can be made- but getting to this point opens opportunities to further enhance the image. Many of these special enhancements are highlighted in PixInsight Horizons. 

This video demonstrates a method of applying differential color saturation based on hue in order to improve color visibility of features in the object. 

Shown below are is the process Adam typically uses to blend color with luminance data. This method is likely not one that is typically shown... but shows that simple innovations can lead to consistent and beneficial results.

In one of the showiest of the fundamental processing steps, HDRMT is applied to the luminance image in order to gain great contrast in the brightest features of interest and moderate the brightness so that vivid color can be blended in later.

This section features a solution for the removal of a (large) dust mote that still appears after flat field corrections. This demonstration is included for completeness, but is not truly a fundamental step. However, there are *always* problems in the course of processing data and finding good solutions certainly is a fundamental skill to strengthen.  

PixInsight's Deconvolution process is a sophisticated tool with many options for interacting with data. This is one of the few multi-step techniques found in the PixInsight Fundamental set of processing tasks.

This video demonstrates the versatility and power of PixInsight's DBE process to minimize non-uniform backgrounds in astronomical data.

This video first shows how to use Photometric Color Calibration and then uses DBE to minimize color gradients. 

The Image Integration process is used to combine the individual LRGB channels with proper rejection. Seeing the results of this process is really the first big reveal of this astrophotographic journey. 

In this video the mathematical rejection of problems (dust donuts in this case) is accomplished by taking advantage of low range and large scale rejection features of Image Integration in the next step. This is an Adam Block innovation by which areas to be rejected are manually identified and processed subsequently.

This video describes the process of registering images in PixInsight. 

This video is about SubFrame Selector in PixInsight Fundamentals.