🚀 go-pugleaf

The images produced in camera are also discreetly produced. Then they are stacked so that the total output for the information part = 1. So, if you shoot, say 4 shots, each shot generates 1/4 the information.

The key is that the information is coincident, that is, there is no variation between the information content except for the amplitude. If there is any difference at all, that difference will be seen as noise.

When C3 Extended came out, there was a routine by which one could do a series of shots with fixed camera location but certain variations such as cars or people or ??? which do not repeat from frame to frame. Summing all those frames in the tool provided would magically remove those elements, but not perfectly. That is the process. When you are stacking the star photos, I don't think you want to remove anything at all from the frames because you are exposing over a pretty long time frame and the individual frames are not identical. When I want to remove noise, the noise is the element that differs frame to frame, in a Gaussian distribution (hopefully!), but the information, say a building,is identical. Obviously, you need a firm platform so I only try this with tripod shots. I'm sure that an algorithm can be derived to do this with hand held images but the noise reduction would suffer.

Essentially, this is an analog process, so the digital implementation has to account for that.

The key to understanding is to ask yourself: What is signal (information) and what is noise, and how do I maximize information? Indeed, how do I know at all what is and if there is information in the data stream.

In the original Star Trek series, there was an episode where the crew had to deal with a hidden renegade, and could not be found with conventional means. So they contrived to set the sensors to read heart beats, and the crew had each of their heart patterns recorded, so that they could be nulled out ie, theirs were "noise". Eventually, only one beat was left and voila! (or is it viola? Ramon?? )