This year at PhotoCamp, I gave a short overview of the concept of computational photography, how it stands to impact digital photography in the years to come. Along with my talk, Andrew Ferguson discussed the ins and outs of blogging about photography, and Duane Storey gave one of the best non-technical overviews of HDR imaging I've heard. Kris Krug moderated, and I think a good time was had by all.
Here are my talk slides. I tried to not ramble incoherently about something overly-technical this time, and tried to keep the message clear, and show off something people can go home and try today. Even if the full magic isn't there, they can get a peak and kick the tires.
The story goes something like this: Due to the complexity of darkroom techniques, and the limitations in what kind of image manipulations we can perform optically while exposing the print from the negative, we have come to view the light that falls on the piece of film in the camera (or the sensor) as the final image. In the old days, it was either impractical or impossible to perform much alterations to the image, so it wasn't attempted.
Digital photography requires computers. No matter how hard you rub the CF card on your monitor or printer, you'll never get an image from your camera to appear. For all intents and purposes, your computer is a giant brain capable of applying a vast number of image manipulations photographs.
There is all this computation available, and the most that people can think to do to their photographs after they are taken is to adjust the white balance.
Given this idea, I demonstrated DxO Optics Pro, the RAW processing software I current use. Optics Pro is one of the better steps in the direction of computational photography available to end users. They meticulously measure all the combinations of digital SLRs and major lenses and can correct the optical distortion and noise automatically. All of this can be done with existing tools, but the idea is that it's automatic and just happens when the image is downloaded off the camera.
Finally, I ended with wavefront coding, a more advanced application of the same basic idea. With wavefront coding, a special lens is used produce a blurry image that is recorded by the sensor. However, this blurry image has several interesting qualities to it. 1) The blur is invariant of the distance of the object and 2) the blur can be corrected in software. The result is an unblurred object with unlimited depth of field, without stopping down the lens to a small aperture, which can be very useful.
It's a very interesting area of work, and a large component of my PhD research. I can't wait to see and share more about it in the future.