Process 2 is all about getting organized and conquering what was perceived as the biggest issue - the fact that Meade's drizzle could not track an object if its path changed more than a 45° from it's original direction.  This meant that even if I had 200 images of an object, I could at best drizzle 25 of them together into a resultant image of quality.

Because I knew I was having problems, I downloaded several other softwares to experiment with the images I had captured.  I found that they had their requirements and drawbacks.  The first was the file names generated by the Meade software.  I wrote a quick program to identify a set of files in an observation and automatically rename the files to a more sensible naming system. 

I realized that if I could use RegiStax to track an object, that maybe I could "offset" each FITS image by the number of pixels the object had moved from the original position.  If I could add pixels on all four sides of the image in such a way so that the resulting images all had the tracked object of interest in exactly the same location in each image, then I could use the exceptional Meade drizzle function on an unlimited number of images.  This technique could alleviate the Meade drizzle deficiency.

So I wrote a program to read the RegiStax project files and find the object tracking information.  It used the tracking to read each FITS image and create a new output image with the object in the same location.  I decided I could add black pixels along the edges of each image.  This really worked well as can be seen in the Process 2 images shown.

I also wrote another program to convert FITS Float files to FITS Integer, as RegiStax required the Integer format.

At this point, I decided that I needed a better way to track all the images I had taken and to manage them into projects, allowing me to review old work, and see if new processes could be used on old images to produce better results. 

Getting organized also meant finding a way to place all of the image files onto a hard disk on a server in such a way as to not require terabits of storage and providing an index for fast access.

The concept was that each series of images made on a particular night would be referred to as an Observation.  The Raw or Uncombined or other images would be stored in a folder with the name of the type of image files stored.  A database would contain information about each observation including object code and name, the folder where the images are kept, the image descriptors like CYMG/Luminosity, CYMG/Mono, pixel dimension, exposure time, number of images, etc.

The next realization was that it is perfectly aok to drizzle images from two different observations, even on two different nights, as long as the images are identical (hence the need for full set of image attributes in the database).  This simply means that the relationship between Projects and Observations is that a Project can contain images from one or more observations of the same object with same image attributes.

This software has been written for identifying images captured by the Envisage software and to move them to the server hard disk, while cataloging the images in an observation data base.

The step to allow a project to be created from images from multiple observations has not been written to date - 8/20.  It would be nice if it had a slide sorter feature that would allow a user to easily discard images that are inferior.

The author is not suggesting or considering that the reader of this site should or would build software to perform these features - writing software is not for the general public to attempt (without great frustration).  And, no, my software is not available at this time.  I really wish someone has already written a software that does all of this cataloging and post processing.

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