Phase recovery (PR) refers to calculating the phase of the light field from its intensity
measurements. As exemplified from quantitative phase imaging and coherent diffraction …

Optical imaging systems have greatly extended human visual capabilities, enabling the
observation and understanding of diverse phenomena. Imaging technologies span a broad …

Scalable, high-capacity, and low-power computing architecture is the primary assurance for
increasingly manifold and large-scale machine learning tasks. Traditional electronic artificial …

Nonlinear encoding of optical information can be achieved using various forms of data
representation. Here, we analyze the performances of different nonlinear information …

Wireless sensing of the wave propagation direction from radio sources lays the foundation
for communication, radar, navigation, etc. However, the existing signal processing paradigm …

Complex field imaging, which captures both the amplitude and phase information of input
optical fields or objects, can offer rich structural insights into samples, such as their …

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts
from input images. In general, digital image denoising algorithms, executed on computers …

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path
length information of transparent specimens for various applications in biology, materials …

Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront
distortions, with applications ranging from imaging to beam focusing. Here, we present a …

Optical neural networks (ONN) are experiencing a renaissance, driven by the transformative
impact of artificial intelligence, as arithmetic pressures are progressively increasing the …