CS: Integral Pixel Cameras and Differential Image Motion

Aha!, a new cheaply made compressive sensing hardware, an Integral Pixel Camera that can evaluate Differential Image Motion. I like it already especially since it obtains parameters for the field of view without performing an image reconstruction. The attendant paper presenting it is:

Compressive sensing and differential image motion estimation by Nathan Jacobs, Stephen Schuh, and Robert Pless. The abstract reads:

Compressive-sensing cameras are an important new class of sensors that have different design constraints than standard cameras. Surprisingly, little work has explored the relationship between compressive-sensing measurements and differential image motion. We show that, given modest constraints on the measurements and image motions, we can omit the computationally expensive compressive-sensing reconstruction step and obtain more accurate motion estimates with significantly less computation time. We also formulate a compressive-sensing reconstruction problem that incorporates known image motion and show that this method outperforms the state-of-the-art in compressive-sensing video reconstruction.

I have added it to the compressive sensing hardware page. Many of the references are familiar but I think it is missing a reference to the Feature Specific Imaging paper. From that train of thought, I like the following presentation of Mark Neifeld made at the Duke-AFRL Meeting a year ago entitled Adaptation for Task-Specific Compressive Imaging and especially this slide:

The attendant video of this presentation is here.