Integrated Calendar

Traditional photography used to be constrained by the need to have a lens focusing light rays onto a film plane as sharply and cleanly as possible. The light recorded at the film plane is the final output image. The rapid development of digital photography is removing these constraints. The recorded data is no longer the final output and post processing computation can be applied to decode the data captured at the sensor plane. This allows us to overcome classical photography problems such as defocus and depth of field, motion blur, spatial and temporal resolution and noise. It also facilitates the acquisition of additional information such as depth and viewpoint variation (the light field). The increasing flexibility of digital photography has lead to the development of a large variety of computational cameras and image acquisition paradigms.

In this talk I will demonstrate some of the challenges and solutions addressed by computational photography systems. I will then focus at a concrete example and demonstrate our work on extended depth of field imaging.

Depth of field (DOF), the range of scene depths that appear sharp in a photograph, poses a fundamental tradeoff in photography---wide apertures are important to reduce imaging noise, but they also increase defocus blur. Recent advances in computational imaging such as wavefront coding or coed aperture cameras modify the acquisition process to extend the DOF through deconvolution. Because deconvolution quality is a tight function of the frequency power spectrum of the defocus kernel, designs with high spectra are desirable. We study how to design effective extended-DOF systems, and show an upper bound on the maximal power spectrum that can be achieved. We analyze defocus kernels in the 4D light field space and show that in the frequency domain, only a low-dimensional 3D manifold contributes to focus. Thus, to maximize the defocus spectrum, imaging systems should concentrate their limited energy on this manifold. We review several computational imaging systems and show either that they spend energy outside the focal manifold or do not achieve a high spectrum over the DOF. Guided by this analysis we introduce the lattice-focal lens, which concentrates energy at the low-dimensional focal manifold and achieves a higher power spectrum than previous designs. We have built a prototype lattice-focal lens and present extended depth of field results.