Recent advances in materials, devices and fabrication technologies have led to an emerging class of solid-state sensors that can detect individual photons in space and time. Thanks to their single-photon sensitivity, ultra-fast speed, and rapidly increasing spatial resolutions, these new single photon sensors (SPS) have great potentials in a wide range of applications, including fluorescence-based bio-imaging, time-of-flight 3D computer vision, high-speed videography, and astronomy. The goal of this project is to build rigorous signal processing foundations for optical imaging based on the emerging SPS scheme.
Analogous to silver-halide grains in photographic film, each pixel of the SPS has a binary response, revealing only one-bit and stochastic information of the local light intensity. With an array of pixels and high temporal sampling rates, the SPS generates a massive spatiotemporal volume of bits that sample and encode the original visual information. The investigator studies models, theory, and algorithms in signal sampling and inference to address the challenges associated with the SPS. Specific objectives of this project involve: (1) establishing sampling theorems for the SPS in acquiring light intensity fields of given spatiotemporal bandwidths; (2) identifying performance bounds and the precise tradeoffs between imaging performance and key device metrics; (3) designing adaptive sensing schemes to improve imaging performances; and (4) developing both offline and online image formation algorithms that can efficiently "decode" the massive bitstreams generated by the SPS.
