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Space Computer Corporation

www.spacecomputer.com
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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.


Ratliff B.M.,Space Computer Corporation | Lemaster D.A.,Air Force Research Lab
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

Pixel-to-pixel response nonuniformity is a common problem that affects nearly all focal plane array sensors. This results in a frame-to-frame fixed pattern noise (FPN) that causes an overall degradation in collected data. FPN is often compensated for through the use of blackbody calibration procedures; however, FPN is a particularly challenging problem because the detector responsivities drift relative to one another in time, requiring that the sensor be recalibrated periodically. The calibration process is obstructive to sensor operation and is therefore only performed at discrete intervals in time. Thus, any drift that occurs between calibrations (along with error in the calibration sources themselves) causes varying levels of residual calibration error to be present in the data at all times. Polarimetric microgrid sensors are particularly sensitive to FPN due to the spatial differencing involved in estimating the Stokes vector images. While many techniques exist in the literature to estimate FPN for conventional video sensors, few have been proposed to address the problem in microgrid imaging sensors. Here we present a scene-based nonuniformity correction technique for microgrid sensors that is able to reduce residual fixed pattern noise while preserving radiometry under a wide range of conditions. The algorithm requires a low number of temporal data samples to estimate the spatial nonuniformity and is computationally efficient. We demonstrate the algorithm's performance using real data from the AFRL PIRATE and University of Arizona LWIR microgrid sensors. © 2012 SPIE.


Ratliff B.M.,Space Computer Corporation | Kaufman J.R.,Space Computer Corporation
Optical Engineering | Year: 2015

Hyperspectral image data suffer from pixel-to-pixel response nonuniformity that degrades the imagery in the form of columnated striping noise. This nonuniformity, or fixed pattern noise (FPN), is typically compensated for through flat-field calibration procedures. FPN is a particularly challenging problem because the detector responsivities drift relative to one another in time, requiring that the sensor be periodically recalibrated. Both the rate and severity of the drift depend on a host of factors that result in varying levels of residual calibration error being present within the data at all times. Scene-based nonuniformity correction (SBNUC) algorithms estimate and remove FPN by exploiting content within the scene data and are often necessary to acceptably remove sensor artifacts for subpixel target detection applications. We present results from two SBNUC techniques that reduce residual FPN and improve target signal-to-clutter ratio. We make the observation that temporally reordering the data in conjunction with the use of spatial ratios or differentials results in algorithms that require a low number of temporal data samples to reliably correct for FPN with minimal introduction of image artifacts. Additionally, application of the algorithms within the principal components domain can further improve their correction ability. © 2015 Society of Photo-Optical Instrumentation Engineers (SPIE).


Grant
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.


Grant
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


Grant
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.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 723.18K | Year: 2011

ABSTRACT: 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 approach addresses both key areas identified in the SBIR topic solicitation by leveraging novel scene-based algorithms for which we developed proof-of-concept examples and processes during the Phase I program. These concepts 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. The proof-of-concept methods developed under the Phase I program were applied to surrogate airborne data as well as ARTEMIS imagery. These methods are adaptable beyond hyperspectral imagers to other imaging modalities including push broom, whisk broom, staring, step stare, and other types of imagers. The additional modalities will be developed under the Phase II program. A stand-alone prototype implementation will be built to demonstrate the performance. An embeddable prototype will also be developed to demonstrate maturity and flight readiness of the software. 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. We anticipate that future space-based images, including potential flight experiments will make use of the investment by the Air Force into this technology. 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. We anticipate that our product will be useful to commercial imagery providers for both space-based and airborne imagers. The commercial approach is to provide the tools and services to the sensor providers as opposed to consumers of the imagery. The technology and software may be sold or licensed to these providers under our commercialization plan.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 100.00K | Year: 2011

Continuous surveillance of selected targets from electro-optical sensors on aircraft and unmanned aerial vehicles (UAVs) are providing significant potential in tactical situation awareness and threat monitoring applications. Situations of interest include movement of vehicles, material, personnel and equipment as well as civilian or military vehicles. Recent capabilities developed include the use of wide-area framing systems combined with image registration and multi-track processing to monitor moving targets. A practical challenge encountered by such systems in a complex environment (e.g., a city) is maintaining the correct association between successive observations of the same target over long time periods or through periods of obscuration or missed coverage. HSI sensors for tracking have the potential to improve the ability to maintain/disambiguate tracks and reacquire lost tracks. Space Computer Corporation, in conjunction with our subcontractor Bodkin Design & Engineering, propose to develop a system design for spectral tracking of moving targets. Our approach is based on the use of the new generation of staring video hyperspectral sensors in conjunction with color cameras and/or wide-area persistent surveillance sensors for tracking. This approach will be compared to alternative methods based on scanning, sequential (temporal) filter-based approaches and Fourier transform methods against the desired system requirements. BENEFIT: Anticipated benefits of our proposed approach include significant improvements in capability for continuous monitoring of specific threat targets moving in complex backgrounds, through incorporation of fine-scale hyperspectral signature information and discriminants into a motion-based target tracking architecture. Potential military applications include: (1) real-time detection, tracking and identification of designated vehicles and dismounts, (2) wide-area persistent surveillance from remote airborne platforms, and (3) identification and mapping of temporally evolving threats such as chemical weapon releases. Potential Government applications include 1) monitoring areas for illicit activities, such as drug transactions, 2) monitoring borders to keep track of suspected illegal border crossings and 3) monitoring industrial processes. Potential commercial applications include site security and intrusion detection, real-time traffic monitoring, air and water pollution effluent tracking, and airborne surveillance for law enforcement and disaster relief.


Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 100.00K | Year: 2011

ABSTRACT: techical abstract placeholder BENEFIT: anticipated benefits placeholder


Grant
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.

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