Relatively little work has been performed to investigate the potential of polarization techniques to provide contrast enhancement in natural scenes. Largely, this is because film is less accurate radiometrically than digital CCD FPA sensing devices. Such enhancement is additional to that provided by between-band differences for multiband data. Recently, Kodak has developed several digital imaging cameras which were intended for professional photographers. The variant we used produced images in the green, red and near infrared, simulating CIR film. However, the application of linear drivers to read the data from the camera into the computer has resulted in a device which can be used as a multiband imaging polarimeter. Here we examine the potential of digital image acquisition as a potential quantitative method to obtain new information additional to that obtained by multiband or even hyperspectral imaging methods. We present an example of an active on-going research program.
Presented in this paper is a methodology that has been used in development of a model-based computer vision system. The methodology focuses on problem solving while using commercial off-the-shelf computer vision software.
Relatively little work has been performed to investigate the potential of polarization techniques to provide contrast enhancement in natural scenes. Historically, this has been because film is less accurate radiometrically than digital CCD FPA sensing devices. Such enhancement is additional to that provided by between-band differences for multiband data. In the mid 1990s, Kodak developed several digital imaging cameras, which were intended for professional photographers. The variant we used produced images in the green, red and near infrared, simulating CIR film. However, the application of linear drivers to read the data from the camera into the computer resulted in a device, which can be used as a portable multiband imaging polarimeter. Here we present examples to examine the potential of digital image acquisition as a potential quantitative method to obtain new information on natural landscapes additional to that obtained by multiband or even hyperspectral imaging methods.
Relatively little work has been performed to investigate the potential of polarization techniques to provide contrast enhancement information for feature mapping, shadow penetration, water penetration or target detection, identification and recognition. Largely, this is because film is less accurate radiometrically than digital CCD FPA sensing devices. Recently, Kodak has developed several digital imaging cameras which were intended for professional photographers. However, the application of linear drivers* to read the data from the camera into the computer has resulted in a device which can be used as a multiband imaging polarimeter. Here we examine the potential of digital image acquisition as a potential quantitative method to obtain new information uncorrelated with that obtained by more conventional multiband or monochromatic imaging methods. We present promising examples of an active on-going research program.
Operational reconnaissance technical organizations are burdened by greatly increasing workloads due to expanding capabilities for collection and delivery of large volume near-real-time multisensor/multispectral softcopy imagery. Related to the tasking of reconnaissance platforms to provide the imagery are more stringent timelines for exploiting the imagery in response to the rapidly changing threat environment being monitored. The development of a semi-automated softcopy multisensor image exploitation capability is a critical step towards integrating existing advanced image processing techniques in conjunction with appropriate intelligence and cartographic data for next generation image exploitation systems. This paper discusses the results of a recent effort to develop computerassisted aids for the image analyst (IA) in order to rapidly and accurately exploit multispectral/multisensor imagery in combination with intelligence support data and cartographic information for the purpose of target detection and identification. A key challenge of the effort was to design and implement an effective human-computer interface that would satisfy any generic IA task and readily accomodate the needs of a broad range of lAs. .Purpose of the laboratory prototype system SAMME is a laboratoiy prototype system that provides advanced techniques to assist the IA to more rapidly and reliably detect, classify, and identify military targets of interest from temporally-coincident multisensor (e.g., SAR, IR, visible band, multispectral, etc.) imagery. Conventional image processing capabilities are combined with state-of-the-art algorithms for automatic target detection, cartographic area limitation, retrieval and graphical presentation of intelligence information overlays with modern image display technology. The primary contextual information used by SAMME includes: finished intelligence (e.g., military installations, military units, and equipment capabilities); terrain/cartographic data (terrain slope, lines of communication, vegetation, and soils), and imagery-related data (collection parameters, weather conditions, and geodetic control). The contextual information is utilized to cue the IA to probable target locations as an aid for the interpretation of target-related events. These features of SAMME are integrated within a modern graphical user interface that emphasizes user-centered control of the exploitation aids by the IA as opposed to enforcing a rigid regime of image exploitation procedures.To effectively demonstrate and evaluate the utility of SAMME's interactive techniques, an operational environment has been developed to support end-to-end imagery exploitation which includes support for: task and mission requirements, P1 keys, shoebox archive, geopositioning and mensuration, image annotation, and report generation. The SAMME laboratory prototype serves as a technology transfer vehicle for demonstrating and promoting the potential effectiveness of computer aids for image analysts from a broad spectrum of operational imagery e...
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