Coded Computational Photography

Computational Photography is an emerging multi-disciplinary field that is at the intersection of optics, signal processing, computer graphics+vision, electronics, art, and online sharing in social networks. The field is evolving through three phases:

Epsilon Photography -- The first phase was about building a super-camera that has enhanced performance in terms of the traditional parameters, such as dynamic range, field of view or depth of field. Due to limited capabilities of a camera, the scene is sampled via multiple photos, each captured by epsilon variation of the camera parameters. It corresponds to the low-level vision: estimating pixels and pixel features.

Coded Photography -- The second phase is building tools that go beyond capabilities of this super-camera. The goal here is to reversibly encode information about the scene in a single photograph (or a very few photographs) so that the corresponding decoding allows powerful decomposition of the image into light fields, motion deblurred images, global/direct illumination components or distinction between geometric versus material discontinuities. This corresponds to the mid-level vision: segmentation, organization, inferring shapes, materials and edges.

Essence Photography -- The third phase will be about going beyond the radiometric quantities and challenging the notion that a camera should mimic a single-chambered human eye. Instead of recovering physical parameters, the goal will be to capture the visual essence of the scene and analyze the perceptually critical components. Essence Photography may loosely resemble depiction of the world after high level vision processing. It will spawn new forms of visual artistic expression and communication.