Journal
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
Volume 3, Issue 3, Pages 384-397Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCI.2016.2593662
Keywords
Computational photography; binary mask; image reconstruction; infrared camera
Funding
- NSF [CCF1117939, CCF1527501, CCF-1502875]
- DARPA REVEAL Grant [HR0011-16-C-0028]
- ONR DURIP Grant [N00014-15-1-2878]
- ONR Grant [N00014-15-1-2735]
- ARO MURI [W911NF0910383]
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1502875] Funding Source: National Science Foundation
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FlatCam is a thin form-factor lensless camera that consists of a coded mask placed on top of a bare, conventional sensor array. Unlike a traditional, lens-based camera, where an image of the scene is directly recorded on the sensor pixels, each pixel in FlatCam records a linear combination of light from multiple scene elements. A computational algorithm is then used to demultiplex the recorded measurements and reconstruct an image of the scene. FlatCam is an instance of a coded aperture imaging system; however, unlike the vast majority of related work, we place the coded mask extremely close to the image sensor that enables thin and flat form-factor imaging devices. We employ a separable mask to ensure that both calibration and image reconstruction are scalable in terms of memory requirements and computational complexity. We demonstrate the potential of the FlatCam design using two prototypes: one at visible wavelengths and one at infrared wavelengths.
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