Fundamental Bounds of Information in Photon Starved Passive Multidimensional Imaging and Recognition in the Presence of Environmental Degradation
Abstract
There have been great advances in the development of image sensors, including exotic imagers such as those in different spectral domains, polarimetric cameras, photon counting arrays, Electron Multiplying (EM) CCD cameras, etc. However, conventional image sensing even when using the most advanced exotic imagers may not perform well in degraded environment or in complex scenarios such as the presence of obscurations and occlusions, and noisy scenes with low SNR targets. Conventional imaging loses much of the information contained in captured photons, such as statistical properties of photons, angular direction of the rays, 3D structural, polarimetric, and multi-spectral information of the scene. Thus, imaging, recognition, and tracking of objects in degraded environments such as low light, occlusions, fog, brown-out conditions, etc. may not be possible using conventional imaging. LiDAR Imaging in degraded environment is not ideal either as LiDAR may not perform well in degraded environment such as fog. In addition, LiDAR is not covert and not suitable for persistent surveillance. Passive multidimensional imaging may remedy the aforementioned problems by capturing and exploiting a vast array of information otherwise lost in conventional sensing approaches to provide an effective high-performance imaging system for use in challenging environments using low-cost distributed sensors.We propose to investigate a comprehensive theoretical foundation to understand the fundamental bounds of information in passive multidimensional imaging in the presence of degraded environments. We shall consider the theoretical bounds of information with multiple degrees of freedom such as angular direction of the rays, polarization, multiple spectral domains (visible and IR), statistical properties of photons, and the scene statistical characteristics. The investigation will be performed assuming non-ideal conditions in terms of uncertainties created by obscurations and occlusions, scattering media, sensor noise, system noise, photon statistics, and the scene statistical characteristics.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502110333
Entities
People
- Bahram Javidi
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Connecticut