Intro to Python Image Processing in Computational Photography
Computational photography is about enhancing the photographic process with computation. While we normally tend to think that this applies only to post-processing the end result (similar to photo editing), the possibilities are much richer since computation can be enabled at every step of the photographic process—starting with the scene illumination, continuing with the lens, and eventually even at the display of the captured image. This is important because it allows for doing much more and in different ways than what can be achieved with a normal camera. It is also important because the most prevalent type of camera nowadays—the mobile camera—is not particularly powerful compared to its larger sibling (the DSLR), yet it manages to do a good job by harnessing the computing power it has available on the device. We’ll take a look at two examples where computation can enhance photography—more precisely, we’ll see how simply taking more shots and using a bit of Python to combine them can create nice results in two situations where mobile camera hardware doesn’t really shine—low light and high dynamic range.
