Hardie R.C.,University of Dayton |
LeMaster D.A.,Air Force Research Lab |
Ratliff B.M.,Space Computer Corporation
Optics Express | Year: 2011
Imagery from microgrid polarimeters is obtained by using a mosaic of pixel-wise micropolarizers on a focal plane array (FPA). Each distinct polarization image is obtained by subsampling the full FPA image. Thus, the effective pixel pitch for each polarization channel is increased and the sampling frequency is decreased. As a result, aliasing artifacts from such undersampling can corrupt the true polarization content of the scene. Here we present the first multi-channel multi-frame super-resolution (SR) algorithms designed specifically for the problem of image restoration in microgrid polarization imagers. These SR algorithms can be used to address aliasing and other degradations, without sacrificing field of view or compromising optical resolution with an anti-aliasing filter. The new SR methods are designed to exploit correlation between the polarimetric channels. One of the new SR algorithms uses a form of regularized least squares and has an iterative solution. The other is based on the faster adaptive Wiener filter SR method. We demonstrate that the new multi-channel SR algorithms are capable of providing significant enhancement of polarimetric imagery and that they outperform their independent channel counterparts. © 2011 Optical Society of America.
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 749.52K | Year: 2012
ABSTRACT: Field measurement campaigns typically deploy numerous sensors having different spatial, temporal, and spectral sampling characteristics. This makes it difficult to process experiment data when a phenomenon of interest spans multiple sensors. There is a clear need for a new software tool that can process sequences of sensor imagery in disparate formats and produce a time sequence of data accurately resampled to a common grid. We demonstrated end-to-end processing performance: 1) cross-sensor spatial registration via scene-based methods; 2) temporal upsampling to common time base via optical flow interpolation; and 3) advanced"fused"image products (e.g. pan sharpened imagery). Our proposed Phase II effort will culminate in a functional prototype software tool. BENEFIT: The first planned product that will incorporate the proposed technology is a Windows Application for ingestion, registering, resampling and fusing multiple imager camera data. This prototype will ingest common format data sets and produce industry standard output data products, including ENVI-compatible data files and standard image and video format imagery (e.g. JPEG, MPEG). This product is intended to demonstrate the capabilities and provide a lead-in to development of custom solutions. We anticipate that probable customers for this initial product include researchers in Government laboratories, Prime Government contractors, Academic researchers, medical imaging device OEM manufacturers and research facilities, biotechnology researchers and commercial providers of manufacturing control and monitoring equipment. Commercial applications include monitoring of manufacturing processes, factories and equipment as well as diagnostic imaging equipment used in the biotechnology and medical device community. This work will benefit the Government directly by providing the processing needed to combine multiple sensor data sets from imagers typically used by AEDC and other government facilities to monitor system and device testing, as well as monitoring and launches.
Agency: Department of Defense | Branch: Defense Advanced Research Projects Agency | Program: SBIR | Phase: Phase II | Award Amount: 749.97K | Year: 2011
Under this Phase II SBIR program Space Computer Corporation (SCC) will enhance the computational performance of key HSI algorithms by utilizing the capabilities of modern commercial Graphics Processor Units (GPUs). This proposal describes an approach that couples the power of GPUs with PC-based processing architectures to significantly shrink the size and weight of airborne, real-time HSI processors and enable powerful new techniques to be implemented on-board the platform. This novel use of GPUs, combined with the recent development of small HSI instruments, will enable cost-effective use of small, inexpensive platforms to support spectral target detection and identification missions previously reserved for large UAV or airborne platforms. We project that Phase II development of a GPU-based HSI processing system will reduce the size of typical on-board processor units to less than 200 cubic inches, compared to the current systems which are about 1,700 cubic inches in volume. This near order-of-magnitude reduction in size and a corresponding weight reduction of nearly a factor of 5 will facilitate the transition of advanced HSI exploitation to the next-generation fleet of small UAVs, putting the power of HSI technology in the hands of more warfighters.
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 100.00K | Year: 2010
Space Computer Corporation (SCC) proposes to address two challenging problems that arise in the operation of space-based electro-optical and infrared (EO/IR) sensor systems: (a) On-orbit refinement and maintenance of sensor calibration, and (b) Accurate geo-location of terrestrial imagery acquired from a space platform. Our proposed approach will address both key areas identified in the SBIR topic solicitation by leveraging novel scene-based algorithms and operational concepts that have been previously demonstrated for ground-based and airborne imaging systems, and have the potential to be automated in on-board processor hardware. Successful development of these methods for space-based remote sensing applications would significantly reduce the timescales required to provide high-fidelity, precisely located image products from sensors deployed for Operationally Responsive Space (ORS) missions. As the provider of the on-board sensor processor software for the recently launched TACSAT-3 ARTEMIS payload, SCC is in a unique position to address these critical issues based on our experience with real-world EO imagery acquired from a spacecraft platform, plus our first-hand knowledge of on-board data processing capabilities and constraints. BENEFIT: Successful development of these methods for space-based remote sensing applications would significantly reduce the timescales required to provide high-fidelity, precisely located image products from sensors deployed for Operationally Responsive Space (ORS) missions. Automated methods for precision pointing and geo-location calibrations is also directly applicable to existing sensor systems, such as SPIRITT, HYCAS, and COMPASS, as well as those under development, such as ACES-HY. Scene-based radiometric calibration would also apply to these and other sensors. In addition to addressing pressing needs for DoD applications, commercial use of space-based imagery for GIS applications would also present a transition opportunity for the technology developed under this SBIR program.
Agency: Department of Energy | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 950.57K | Year: 2010
Long-term continuous moving-target surveillance from airborne electro-optical sensors provides critical information for tactical awareness situations. Tracking civilian vehicles in urban environments is a challenging problem for existing systems, which generally rely on high-resolution video imagery to identify targets by their spatial characteristics. It is difficult for current spatial-based trackers to re-acquire target lock once the subject has been obscured from view for even moderate lengths of time. The goal of this effort is to demonstrate the exploitation of a vehicle target