Lensless imaging provides opportunities to design imaging systems free from the constraints
imposed by traditional camera architectures. Due to advances in imaging hardware …

Abstract Machine vision faces bottlenecks in computing power consumption and large
amounts of data. Although opto-electronic hybrid neural networks can provide assistance …

The race for miniature color cameras using flat meta-optics has rapidly developed the end-to-
end design framework using neural networks. Although a large body of work has shown the …

Deconvolution can be used to obtain sharp images or volumes from blurry or encoded
measurements in imaging systems. Given knowledge of the system's point spread function …

Moving computation units closer to sensors is becoming a promising approach to
addressing bottlenecks in computing speed, power consumption, and data storage. Pre …

One of the holy grails of neuroscience is to record the activity of every neuron in the brain
while an animal moves freely and performs complex behavioral tasks. While important steps …

Compressive lensless imagers enable novel applications in an extremely compact device,
requiring only a phase or amplitude mask placed close to the sensor. They have been …

Lensless cameras are a novel class of computational imaging devices, in which the lenses
are replaced with a thin mask to achieve ultra-compact and low-cost hardware. In this paper …

End-to-end optimization of diffractive optical elements (DOEs) profile through a digital
differentiable model combined with computational imaging have gained an increasing …

Fresnel zone aperture (FZA) lensless imaging encodes the incident light into a hologram-
like pattern, so that the scene image can be numerically focused at a long imaging range by …