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.
A fuzzy logic based data association routine has been developed. The concept is based on very simple fuzzy logic implementation. The resulting technique is intended as an enhancement to current data association routin...
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A fuzzy logic based data association routine has been developed. The concept is based on very simple fuzzy logic implementation. The resulting technique is intended as an enhancement to current data association routines when added information such as sensor blockage and forbidden terrain knowledge can be incorporated into the system.
The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensorfusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor i...
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ISBN:
(纸本)0819431931
The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensorfusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the FLIPS concept targets interceptor functionality;other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an "intelligent" processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.
This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect...
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ISBN:
(纸本)0819431931
This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability.
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 Multi-sensorfusion Management (MSFM) algorithm positions multiple, detection-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method, ...
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ISBN:
(纸本)0819431931
The Multi-sensorfusion Management (MSFM) algorithm positions multiple, detection-only, passive sensors in a two-dimensional plane to optimise the fused probability of detection using a simple decision fusion method, previously the MSFM algorithm was evaluated on two synthetic problem domains comprising of both static and moving targets(1). In the original formulation the probability distribution of the target location was modelled using a non-parametric approach. The logarithm of the fused detection probability was used as a criterion function for the optimisation of the sensor positions. This optimisation used a straightforward gradient ascent approach, which occasionally found local optima. Following the placement optimisation the sensors were deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution could then be updated using the method of sampling, importance re-sampling (SIR). In the current work the algorithm is extended to admit a richer variety of behaviour. More realistic sensor characteristic models are used which include detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. In this paper the performance of the updated MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application(2) in which the placement of the sensors is carried out incrementally, allowing for the optimisation of both the location and the number of sensors to be deployed.
Many multi-sensor target tracking systems are developed under the assumptions that data association is too complex and computational requirement is too excessive for centralized fusion approaches to be practical. In a...
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Many multi-sensor target tracking systems are developed under the assumptions that data association is too complex and computational requirement is too excessive for centralized fusion approaches to be practical. In addition, it is also assumed that the noise component is relatively small, that there are no missed detection and that the scanning interval is relatively short, etc. Many multi-sensor tracking systems have been shown to be able to perform effectively when tested with simulated data generated under these assumptions. However, careful investigation into the characteristics of several sets of real data reveals that these assumptions cannot always be made validly. In this paper, we first describe the characteristics of a real multisensor tracking environment and explain why existing systems may not be able to perform their task effectively in such environment. We then present a data fusion technique that can overcome some of the weaknesses of these systems. This technique consists of three steps: (i) estimation of synchronization error using an adaptive learning approach;(ii) adjustment of measured positions of a target in case of missed detection;and (iii) prediction of the next target position using a fuzzy logic based algorithm. For performance evaluation, we tested the technique using different sets of real and simulated data. The results obtained are very satisfactory.
This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect...
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This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability.
The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensorfusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor i...
详细信息
The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensorfusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an 'intelligent' processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.
Facing the increasing availability of remote sensing imagery, the compression of information and the combining of multi-spectral and multi-sensor image data are becoming of greater importance. This paper presents a ne...
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ISBN:
(纸本)0819431931
Facing the increasing availability of remote sensing imagery, the compression of information and the combining of multi-spectral and multi-sensor image data are becoming of greater importance. This paper presents a new image fusion scheme based on PCA and multi-resolution analysis of wavelet theory for fusing high-resolution panchromatic and multi-spectral images. It is done in two ways: a). By replacing some wavelet coefficients of k-principal components by the corresponding coefficients of the high-resolution panchromatic image;b). By adding the wavelet coefficients of the high-resolution panchromatic image directly to k-principal components. The proposal approach is used to fuse the SPOT panchromatic and Landsat (TM) multi-spectral images. Experimental results demonstrate that the proposal approach can not only preserve all the spectral characteristics of the multi-spectral images, but can also improve their definition and spatial quality. Compared with the PCA fusion method, the proposal scheme is much better and possesses more capable of adaptability.
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