You are here

Integrated learning-based and regularization-based super resolution for extreme MWIR image enhancement

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0027
Agency Tracking Number: N17A-016-0023
Amount: $1,499,999.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N17A-T016
Solicitation Number: 17.A
Solicitation Year: 2017
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-11-07
Award End Date (Contract End Date): 2021-11-17
Small Business Information
19805 Hamilton Ave
Torrance, CA 90502-0000
United States
DUNS: 625511050
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Tait Pottebaum
 Senior Scientist
 (310) 756-0520
Business Contact
 Nahum Gat
Phone: (310) 756-0520
Research Institution
 Northwestern University
 Stephanie Logaras Stephanie Logaras
633 Clark Street
Evanston, IL 60208-0000
United States

 (847) 491-3003
 Nonprofit College or University

OKSI and Northwestern University propose to develop a single-image super-resolution (SR) methodology for mid-wave infrared (MWIR) imagery that combines learning-based and regularization-based approaches to produce extreme enhancement of low-resolution images. We will also develop a detector-limited imaging system specifically designed to be used with the SR methodology for which even higher levels of image enhancement can be attained. The newly developed SR methodology will directly address the Navy’s desire for variable resolution MWIR imagery achieved through post-processing, as well as the imaging needs of other government agencies. During Phase-I, OKSI and Northwestern University demonstrated a proof-of-concept for the SR methodology and quantified the image enhancement that is attained. In Phase-II, we will build and demonstrate a prototype imaging system with near real-time post-processing for and ROI within the image.

* Information listed above is at the time of submission. *

US Flag An Official Website of the United States Government