Turbulence improvements by combination of dedicated hardware and software
Abstract
Atmospheric optical turbulence, caused by refractive index changes along a path, degrades the quality of EO/IR images, and reduces the performance of detection, identification, and tracking systems. Restoration of degraded images is particularly challenging because refractive index changes depend on atmospheric conditions, vary with the observation direction, and change significantly with time. Current restoration methods based on adaptive optics and deformable mirrors are effective only when degradations are moderate. A more effective image restoration method can increase significantly the operational range of critical ISR images obtained in the maritime atmosphere. This proposal is particularly relevant to Assured C3, Battlespace Awareness, and Integrated Fires - CNOG~20 Priority. InnovationThe innovation of this proposal has two elements: i) the use of multiple images of each scene to characterize thoroughly the degradation introduced by turbulence, and ii) the digital reconstruction of an image where degradation is removed or mitigated, without using moving parts and deformable mirrors. The project will study the feasibility of an innovative image acquisition and processing system that can implement this approach. While observing one scene, a set of images will be produced with several fast cameras each of which will be controlled by a fast wavefront modulator. The different cameras will provide the view of the scene from slightly different angles (spatial diversity) and the wavefront modulator will produce multiple images from each camera with varying optical parameters (phase diversity). This novel technique will produce a set of rich spatial and phase information that has strong potential for effective characterization of turbulence effects. This unprecedented and complex method is now conceivable due to increases in the frame rates of high resolution cameras and wavefront modulators, and a significant reduction in their costs. The PI will configure the imaging system to collect the data and she will develop a model that represents the image degradation. Based on this model she will develop the image processing algorithm that can produce the reconstructed image.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 15, 2019
- Source ID
- N629091912095
Entities
People
- Judith Dijk
Organizations
- Netherlands Organisation for Applied Scientific Research
- Office of Naval Research
- United States Navy