Jan. 31, 2024, 3:43 p.m. | Jingxi Li Yuhang Li Tianyi Gan Che-Yung Shen Mona Jarrahi Aydogan Ozcan

cs.CV updates on arXiv.org arxiv.org

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 absorption and refractive index distributions. However, conventional image sensors are intensity-based and inherently lack the capability to directly measure the phase distribution of a field. This limitation can be overcome using interferometric or holographic methods, often supplemented by iterative phase retrieval algorithms, leading to a considerable increase in hardware complexity and computational demand. …

amplitude capability cs.cv distribution fields image imaging index information insights intensity objects optical physics.app-ph physics.optics processors samples sensors

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne