@article{Li:17,

author = {Fengqiang Li and Huaijin Chen and Adithya Pediredla and Chiakai Yeh and Kuan He and Ashok Veeraraghavan and Oliver Cossairt},

journal = {Opt. Express},

keywords = {Inverse problems; Superresolution; Three-dimensional image processing; Three-dimensional image acquisition; Machine vision},

number = {25},

pages = {31096--31110},

publisher = {OSA},

title = {CS-ToF: High-resolution compressive time-of-flight imaging},

volume = {25},

month = {Dec},

year = {2017},

url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-25-25-31096},

doi = {10.1364/OE.25.031096},

abstract = {Three-dimensional imaging using Time-of-flight (ToF) sensors is rapidly gaining widespread adoption in many applications due to their cost effectiveness, simplicity, and compact size. However, the current generation of ToF cameras suffers from low spatial resolution due to physical fabrication limitations. In this paper, we propose CS-ToF, an imaging architecture to achieve high spatial resolution ToF imaging via optical multiplexing and compressive sensing. Our approach is based on the observation that, while depth is non-linearly related to ToF pixel measurements, a phasor representation of captured images results in a linear image formation model. We utilize this property to develop a CS-based technique that is used to recover high resolution 3D images. Based on the proposed architecture, we developed a prototype 1-megapixel compressive ToF camera that achieves as much as 4{\texttimes} improvement in spatial resolution and 3{\texttimes} improvement for natural scenes. We believe that our proposed CS-ToF architecture provides a simple and low-cost solution to improve the spatial resolution of ToF and related sensors.},

}