The Joint Directors of Laboratories (JDL) Data fusion Group's Data fusion Model is the most widely used method for categorizing data fusion-related functions. This model is modified to facilitate the cost-effectiv...
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The Joint Directors of Laboratories (JDL) Data fusion Group's Data fusion Model is the most widely used method for categorizing data fusion-related functions. This model is modified to facilitate the cost-effective development, acquisition, integration and operation of multi-sensor/multi-source systems. Proposed modifications include broadening of the functional model and related taxonomy beyond the original military focus, and integrating the Data fusion Tree Architecture model for system description, design and development.
The Dempster Shafer (DS) Theory of Evidential Reasoning may be useful in handling issues associated with theater ballistic missile discrimination. This paper highlights the Dempster-Shafer theory and describes how thi...
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The Dempster Shafer (DS) Theory of Evidential Reasoning may be useful in handling issues associated with theater ballistic missile discrimination. This paper highlights the Dempster-Shafer theory and describes how this technique was implemented and applied to data collected by two infrared sensors on a recent flight test.
In both military and civilian applications, increasing interest is being shown in fusing infrared and vision images for improved situational awareness. In previous work, the authors have developed a fusion method for ...
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In both military and civilian applications, increasing interest is being shown in fusing infrared and vision images for improved situational awareness. In previous work, the authors have developed a fusion method for combining the thermal and vision images into a single image emphasizing the most salient features of the surrounding environment. This approach is based on the assumption that although the thermal and vision data are uncorrelated, they are complementary and can be fused using a suitable disjunctive function. This paper, as a continuation of that work, will describe the development of an information based real-time data level fusion method. In addition, applicability of the algorithms that we developed for data level fusion to feature level techniques (e.g., shapes, lines, and edges) will be investigated.
The Common Object Request Broker Architecture (COBRA) has been proven to be effective for application in the Data fusion domain. However, the benefits of this system have not yet been fully realized because of unresol...
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The Common Object Request Broker Architecture (COBRA) has been proven to be effective for application in the Data fusion domain. However, the benefits of this system have not yet been fully realized because of unresolved issues concerning reliability, fault-tolerance and real-time/fast enough QoS behavior of the system. In view of this, an attempt has been made to develop a domain specific environment with the commercially available standard products. The result is a COBRA based infrastructure (CORBIS) that provide interfaces and mechanisms for various applications and services.
Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from mult...
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Availability of different imaging modalities requires techniques to process and combine information from different images of the same phenomena. We present a symmetry based approach for combining information from multiple images. fusion is performed at data level. Actual object boundaries and shape descriptors are recovered directly from raw sensor output(s). Method is applicable to arbitrary number of images in arbitrary dimension.
A decentralized technique in which kinematic information from a radar and infrared imager are fused has been developed. To validate its effectiveness, the technique has been compared to a sequentially based Kalman fil...
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A decentralized technique in which kinematic information from a radar and infrared imager are fused has been developed. To validate its effectiveness, the technique has been compared to a sequentially based Kalman filter via Monte Carlo simulation. The comparison showed that the decentralized technique is a potentially viable alternative.
The potential problem of deterioration in recognition system performance because of imprecise, incomplete, or imperfect training is a serious challenge inherent to most real-world applications. This problem is often r...
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The potential problem of deterioration in recognition system performance because of imprecise, incomplete, or imperfect training is a serious challenge inherent to most real-world applications. This problem is often referred to in certain applications as degradation of performance under off-nominal conditions. This study presents the results of an investigation carried out to illustrate the scope and benefits of information fusion in such off-nominal scenarios. The research covers features in - decision out (FEI-DEO) fusion as well as decisions in - decision out (DEI-DEO) fusion. The latter spans across both information sources (sensors) and multiple processing tools (classifiers). The investigation delineates the corresponding fusion benefit domains using as an example, real-world data from an audio-visual system for the recognition of French oral vowels embedded in various levels of acoustical noise.
Humans exhibit remarkable abilities to estimate, filter, predict, and fuse information in target tracking tasks. To improve track quality, we extend previous tracking approaches by investigating human cognitive-level ...
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Humans exhibit remarkable abilities to estimate, filter, predict, and fuse information in target tracking tasks. To improve track quality, we extend previous tracking approaches by investigating human cognitive-level fusion for constraining the set of plausible targets where the number of targets is not known a priori. The target track algorithm predicts a belief in the position and pose for a set of targets and an automatic target recognition algorithm uses the pose estimate to calculate an accumulated target-belief classification confidence measure. The human integrates the target track information and classification confidence measures to determine the number and identification of targets. This paper implements the cognitive belief filtering approach for sensorfusion and resolves target identity through a set-theory approach by determining a plausible set of targets being tracked.
A System for Systems (SoS) design is introduced for improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems. The physio-associative temporal sensor i...
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A System for Systems (SoS) design is introduced for improving the overall performance, capabilities, operational robustness, and user confidence in Identification (ID) systems. The physio-associative temporal sensor integration algorithm (PATSIA) is used. The SoS architecture proposes dynamic sensor and knowledge-source integration by implementing multiple Emergent Processing Loops (EPL) for Predicting, feature Extracting, Matching, and Searching both static and dynamic databases. These objectives are demonstrated by modeling similar processes from the eyes, ears, and somatosensory channels, through the thalamus, and to cortices as appropriate while using the hippocampus for short-term memory search and storage as necessary.
The work described in this paper focuses on cross band pixel selection as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via QMF sub-band decompo...
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The work described in this paper focuses on cross band pixel selection as applied to pixel level multi-resolution image fusion. In addition, multi-resolution analysis and synthesis is realised via QMF sub-band decomposition techniques. Thus cross-band pixel selection is considered with the aim of reducing the contrast and structural distortion image artefacts produced by existing wavelet based, pixel level, image fusion schemes. Preliminary subjective image fusion results demonstrate clearly the advantage which the proposed cross-band selection technique offers, when compared to conventional area based pixel selection.
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