April 24, 2024, 4:45 a.m. | Libang Chen, Jun Yang, Lingye Chen, Yuyang Shui, Yikun Liu, Jianying Zhou

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.15082v1 Announce Type: cross
Abstract: Recording and identifying faint objects through atmospheric scattering media by an optical system are fundamentally interesting and technologically important. In this work, we introduce a comprehensive model that incorporates contributions from target characteristics, atmospheric effects, imaging system, digital processing, and visual perception to assess the ultimate perceptible limit of geometrical imaging, specifically the angular resolution at the boundary of visible distance. The model allows to reevaluate the effectiveness of conventional imaging recording, processing, and perception …

abstract arxiv cs.cv digital effects imaging media objects optical perception physics.optics processing recording through type visual work

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