The refractive-lens technique has been well developed over a long period of evolution,
offering powerful imaging functionalities, such as microscopes, telescopes, and …

With the rapid development of high-speed communication and artificial intelligence
technologies, human perception of real-world scenes is no longer limited to the use of small …

Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …

Nano-optic imagers that modulate light at sub-wavelength scales could enable new
applications in diverse domains ranging from robotics to medicine. Although metasurface …

Planar digital image sensors facilitate broad applications in a wide range of areas,,,–, and
the number of pixels has scaled up rapidly in recent years,. However, the practical …

Hyperspectral imaging is useful for applications ranging from medical diagnostics to
agricultural crop monitoring; however, traditional scanning hyperspectral imagers are …

Diffractive achromats (DAs) promise ultra-thin and light-weight form factors for full-color
computational imaging systems. However, designing DAs with the optimal optical transfer …

Cameras are designed with a complicated tradeoff between image quality (eg sharpness,
contrast, color fidelity), and practical considerations such as cost, form factor, and weight …

Most modern commodity imaging systems we use directly for photography—or indirectly rely
on for downstream applications—employ optical systems of multiple lenses that must …

Imaging depth and spectrum have been extensively studied in isolation from each other for
decades. Recently, hyperspectral-depth (HS-D) imaging emerges to capture both …