22 August 2017 High-resolution imaging using a translating coded aperture
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Abstract
It is well known that a translating mask can optically encode low-resolution measurements from which higher resolution images can be computationally reconstructed. We experimentally demonstrate that this principle can be used to achieve substantial increase in image resolution compared to the size of the focal plane array (FPA). Specifically, we describe a scalable architecture with a translating mask (also referred to as a coded aperture) that achieves eightfold resolution improvement (or 64∶1 increase in the number of pixels compared to the number of focal plane detector elements). The imaging architecture is described in terms of general design parameters (such as field of view and angular resolution, dimensions of the mask, and the detector and FPA sizes), and some of the underlying design trades are discussed. Experiments conducted with different mask patterns and reconstruction algorithms illustrate how these parameters affect the resolution of the reconstructed image. Initial experimental results also demonstrate that the architecture can directly support task-specific information sensing for detection and tracking, and that moving objects can be reconstructed separately from the stationary background using motion priors.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2017/$25.00 © 2017 SPIE
Abhijit Mahalanobis, Richard Shilling, Robert Muise, and Mark A. Neifeld "High-resolution imaging using a translating coded aperture," Optical Engineering 56(8), 084106 (22 August 2017). https://doi.org/10.1117/1.OE.56.8.084106
Received: 22 April 2017; Accepted: 26 July 2017; Published: 22 August 2017
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Staring arrays

Image resolution

Sensors

Reconstruction algorithms

Coded apertures

Coded aperture imaging

Motion models

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