The number of sensory nodes in the Internet of everything continues to increase rapidly and
generate massive data. The generated information from sensory nodes is much larger than …

Photography is a cornerstone of imaging. Ever since cameras became consumer products
more than a century ago, we have witnessed great technological progress in optics and …

Implantable image sensors have the potential to revolutionize neuroscience. Due to their
small form factor requirements; however, conventional filters and optics cannot be …

Deep learning using convolutional neural networks (CNNs) is quickly becoming the state-of-
the-art for challenging computer vision applications. However, deep learning's power …

Compressive imaging using coded apertures (CA) is a powerful technique that can be used
to recover depth, light fields, hyperspectral images and other quantities from a single …

We capture 4D light field data in a single 2D sensor image by encoding spatio-angular
information into a speckle field (causticpattern) through a phase diffuser. Using wave-optics …

Lensless imaging is a new, emerging modality where image sensors utilize optical elements
in front of the sensor to perform multiplexed imaging. There have been several recent …

Single-shot light field cameras typically sacrifice spatial resolution to sample angular
viewpoints, multiplexing rays onto a 2D sensor array. Using compressive sensing to recover …

Mask-based lensless cameras replace the lens of a conventional camera with a custom
mask. These cameras can potentially be very thin and even flexible. Recently, it has been …

Light fields present a rich way to represent the 3D world by capturing the spatio-angular
dimensions of the visual signal. However, the popular way of capturing light fields (LF) via a …