Equipment does not make images: people do. What people—what you, the astro-imager—bring to the telescope is the skill and knowledge to use equipment effectively. You don't need to wait long before you'll hear someone new to digital imaging whining the complaint: "These images are no good. This telescope/camera/ software is a piece of What you're hearing is a frustrated person attempt ing to place blame on some inanimate objects.
It is admittedly sometimes difficult to analyze an imaging challenge as a problem to solve—but seeking the cause of problems leads to solutions,whereas blaming the equipment does not. (Admittedly, sometimes equipment does leave much to be desired, and a systematic problem-solving approach will reveal this fact.)
In its broad sense, technique means "a manner in which technical details are treated." How should you treat technical details? First, recognize that every such detail matters. Leave out one crucial "detail"—such as precise focus—and nothing else you do will give you good images. Second, look for causes. Good imaging is based on cause and effect. When something goes awry, ask questions. What might have caused this? Whenever you're tempted to say, "Stuff happens," you need instead to say, "Stuff happens because "
Third, work to understand what it is that you're doing. In systems engineering, there's a concept called solution space. Solutions are high spots, failures are low spots. If you wander around changing what you do bit-by-bit in response to your results, your images will get better because you'll be moving toward a peak in solution space. Once you're on a local peak, small changes will make your images get worse. In short, you'll be trapped in techniques that work—but not necessarily the best techniques.
If you understand what you're doing, you may be able to look around to see whether the local peak you're standing on is not the highest peak. Consider this example: A few years ago, it looked like the best way to shoot planetary images was to make lots of short exposures with a 16-bit camera and select the very best image from hundreds taken. To make color images, you made three images with color filters. It was a local peak in solution space, and a rather high peak at that.
Then along came webcams with their tacky little 8-bit images. Even the best webcam images look weak and noisy. But registering and stacking a few hundred of those noisy little images built a high signal-to-noise ratio, and selecting the best hundred from a thousand captured the best moments of seeing. The 8-bit webcam technique peak is higher in solution space than the single best 16-bit image CCD technique—and it's easier to use the webcam, too.
Digital imaging is a dynamic subject. Every time you turn around, there's a new device entering the market that just might be the next shining beacon on a yet-higher peak. But not always. That webcams are great for imaging bright objects with short exposures hardly guarantees that they'll be good for faint targets—summing readout noise over hundreds of photon-starved images simply cannot beat longer integrations. The numbers demand the result.
As you develop your imaging skills, you face a multitude of technical challenges—and solving challenges is what makes imaging so much fun. Pay attention to the details, look for causes, and survey the entire solution space.
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