An inexpensive way to add imaging across a variety of applications, ranging from endoscopy and medical sensing to machine inspection, surveillance, and the IoT.
We describe a new class of lensless, ultra-miniature computational imagers and image sensors employing special optical phase gratings integrated with CMOS photodetector matrices. Because such imagers have no lens, they are ultra- miniature (∼100 μm), have large effective depth of field (1 mm to infinity), and are very inexpensive (a few Euro cents). The grating acts as a two-dimensional visual “chirp” and preserves image power throughout the Fourier plane (and hence preserves image information); the final digital image is not captured as in a traditional camera but instead computed from raw photodetector signals. The novel representation at the photodetectors demands that algorithms such as deconvolution, Bayesian estimation, or matrix inversion with Tikhonov regularization be used to compute the image, each having different bandwidth, space and computational complexities for a given image fidelity. Such imaging architectures can also be tailored to extract application-specific information or compute decisions (rather than compute an image) based on the optical signal. In most cases, both the phase grating and the signal processing can be optimized for the information in the visual field and the task at hand. Our sensor design methodology relies on modular parallel and computationally efficient software tools for simulating optical diffraction, for CAD design and layout of gratings themselves, and for sensor signal processing. These sensors are so small they should find use in endoscopy, medical sensing, machine inspection, surveillance and the Internet of Things, and are so inexpensive that they should find use in distributed network applications and in a number of single-use scenarios, for instance in military theaters and hazardous natural and industrial conditions.
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