Welcome to my new column!
I’m thrilled and honored to be embarking on this monthly blog on Astrophotography for Sky and Telescope. I thought a bit about the title of this blog, “Imaging Foundations”. We wanted a beginners blog, but I hate the term “beginner." If you learn something new, you’re a beginner. You may understand great cosmic mysteries and become a master teacher, but if you learn a single new thing, in that new thing . . . you are a beginner! We are all beginners because we never stop learning. Mastery is not the point where you can't learn any more. Mastery is when you realize you never stop learning, and you embrace it.
My goal is that everyone of all skill levels will learn something new in each of my posts, and so it is for beginners at all levels of experience. Even if you already understand a point I’m trying to make, it’s my hope that you'll at least find a new way of explaining something to other beginners like us.
Another thing about a beginner’s blog is that I can assume very little previous knowledge, so I’ll be focusing on foundational topics that you can build on yourself. I’ve come to find that many advanced imagers have a lot of misconceptions about some of these so-called fundamentals, and I’ve even been wrong about a few of them myself from time to time.
Knowing that, this is going to be a blog about first principles and best practices.
A professor of mine used to tell us that training was for dogs and circus animals, while education was for human beings. I’m not sure I’d go quite that far but, like him, I’ve come to believe that a solid foundational understanding is more useful than a checklist.
I have a few guiding beliefs:
The first is that astrophotography is photography. Photography is art and can be subjective, but it doesn’t have to be — and there is nothing wrong with art. I will never use art as a slur for images I do not like. There is much to the art of astrophotography that I don't feel qualified to pontificate on.
Imaging, on the other hand, is about acquiring data (in my personal view). Getting good data is at least as important as learning how to process it, and in fact I think far too much attention is paid to clever processing techniques and far too little attention is paid to how to get good data. For this reason, I’ll avoid a lot of deep processing topics, and focus on the fundamentals that apply no matter what processing software you use. This brings me to…
PixInsight or Photoshop? People ask me that like they might ask my political affiliation — as if the answer will tell them all they need to know about how I process my data, what my philosophies are, skill level is, etc.
The truth is I use both PixInsight and Photoshop, and it saddens me whenever someone tells me they “only” use DeepSkyStacker or some such, like they are apologizing for it.
Imagine if we were carpenters and we were arguing over whether we should be using hammers all the time or screwdrivers. There is an old saying, “When the only tool you have is a hammer, every problem looks like a nail”.
I have more tools in my toolbox than just a hammer, and I’ll expand on this idea in future posts. I really think false dichotomies do more harm than good. Which is better, DLR or CCD? Color or Monochrome? Reflectors or refactors?
These questions are much like asking which is better a car or a truck? It really depends on what your needs and goals are (maybe a bicycle is actually best!) and we’ll tackle these questions and more in the coming months. It’s going to be a great ride, and I hope you’ll join me here each month!