Sam Hasinoff (CSAIL, MIT)
Wednesday, 4.8.2010, 11:30
Computation is playing an increasingly central role in how we capture and process our images, opening up richer forms of photography that go beyond conventional imaging. Recent examples include merging multiple shots to obtain seamless panoramas, 3D shape, deeper focus, or a wider range of tones. In this talk, I will argue that the future of photography lies in richer capture, paying special attention to our limited budget of light, time, and sensor throughput. By analyzing tradeoffs and limits in imaging, we can develop ways to enrich photography while making efficient use of our cameras.
First, I will address the basic problem of capturing an in-focus image in a fixed time budget. As our analysis shows, the number of shots captured is a crucial determinant of quality, and taking this into account places the conventional camera in a surprisingly favorable light. Second, I will describe how existing cameras can be used more efficiently to capture scenes with a wide range of tones. By adjusting the camera's amplifier as well as its shutter speed, we can achieve upto 10x noise reduction in the darkest parts of the scene. Both of these projects demonstrate how computation can enrich photography, while providing significant gains over the state-of-the-art.