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检索条件"主题词=Image and Data Fusion"

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The Utility of Polarimetry within Passive Military Imaging Systems 14

The Utility of Polarimetry within Passive Military Imaging S...

引用

Conference on Electro-Optical and Infrared Systems - Technology and Applications XIV

作者： Hickman, Duncan L. Smith, Moira I. Kim, Kyung Su Choi, Hyun-Jin Tektonex Ltd Argyll Rd Kilcreggan Scotland Agcy Def Dev Sunamdong Daejeon South Korea

ISBN: (数字)9781510613317

ISBN: (纸本)9781510613317;9781510613300

An ongoing challenge for many military imaging systems is the detection and classification of weak target signatures in a cluttered environment. In such cases, the use of image contrast and relative target motion alone does not always provide a sufficient level of target discrimination to give operational confidence and it is therefore necessary to consider the use of other discriminatory scene information. Polarisation is one such source of information and this paper reports on an extensive series of polarimetric trials undertaken across the visible, NIR, SWIR, MWIR and LWIR spectral bands. Using this data, the benefits and limitations of polarisation discrimination are reviewed in the context of practical military scenarios. It is shown that polarisation signatures vary with viewing geometry and atmospheric conditions. This would lead to an unpredictable performance level if the sensor discrimination was based solely on polarisation. However, by carefully combining polarisation with other scene information, useful operational benefits can be obtained and this is illustrated through a consideration of different data fusion approaches.

关键词： Polarisation Polarimetry Spectral Processing Automatic Target Detection and Recognition (ATD/R) Clutter Suppression EO Sensor Performance Robustness image and data fusion

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Robust fusion-Based Processing for Military Polarimetric Imaging Systems 27

Robust Fusion-Based Processing for Military Polarimetric Ima...

引用

Conference on Automatic Target Recognition XXVII

作者： Hickman, Duncan L. Smith, Moira I. Kim, Kyung Su Choi, Hyun-Jin Tektonex Ltd Argyll Rd Kilcreggan Scotland Agcy Def Dev Sunamdong Daejeon South Korea

ISBN: (纸本)9781510609051;9781510609068

Polarisation information within a scene can be exploited in military systems to give enhanced automatic target detection and recognition (ATD/R) performance. However, the performance gain achieved is highly dependent on factors such as the geometry, viewing conditions, and the surface finish of the target. Such performance sensitivities are highly undesirable in many tactical military systems where operational conditions can vary significantly and rapidly during a mission. Within this paper, a range of processing architectures and fusion methods is considered in terms of their practical viability and operational robustness for systems requiring ATD/R. It is shown that polarisation information can give useful performance gains but, to retained system robustness, the introduction of polarimetric processing should be done in such a way as to not compromise other discriminatory scene information in the spectral and spatial domains. The analysis concludes that polarimetric data can be effectively integrated with conventional intensity-based ATD/R by either adapting the ATD/R processing function based on the scene polarisation or else by detection-level fusion. Both of these approaches avoid the introduction of processing bottlenecks and limit the impact of processing on system latency.

关键词： Polarisation Polarimetry Automatic Target Detection and Recognition EO Sensor Performance Robustness image and data fusion image Enhancement image Metrics

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Evaluation Criteria for image fusion Performance in Different Applications

Evaluation Criteria for Image Fusion Performance in Differen...

引用

International Conference on Industrial Control and Electronics Engineering (ICICEE)

作者： Zeng, Yu van Genderen, J. L. Zhang, Jixian Wang, Guangliang Chinese Acad Surveying & Mapping Beijing 100830 Peoples R China Univ Twente Enschede Netherlands

ISBN: (纸本)9780769547923

image and data fusion is a process dealing with data and information from multiple sources to achieve refined or improved information for decision making. It has wide applications. When images with a similar acquisition time are used, the expected result is to obtain a fused image that retains the spatial resolution from the panchromatic image and color content from the multi-spectral image, to perform land use/cover classification, or to extract geo-spatial information, which can be used in thematic mapping, as well as the establishment and update of geo-spatial databases;when images with different dates are used, the main purpose of image fusion is to detect the changes over a period of time, which can be employed in disaster monitoring, environmental monitoring, land use/cover change detection, etc. Aiming at the two types of applications, this paper discusses and summarizes the evaluation methods for image fusion performance in the level of pixel-based processing and decision-based processing. It also develops a quantitative analysis method for assessment of the pixel-level image fusion for change detection. This method integrates spectral features and spatial texture features which constitute the most important visual content of an image. The main idea of this method is to compare the image similarity between the regions where changed parcels are located and the regions where there is no change using the similarity measure. The practical application examples of the evaluation criteria are also given.

关键词： image Processing image and data fusion Quantitative Analysis Quality Performace Evaluation

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Evaluation Criteria for image fusion Performance in Different Applications

Evaluation Criteria for Image Fusion Performance in Differen...

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International Conference on Industrial Control and Electronics Engineering

作者： Yu ZENG J.L. van GENDEREN Jixian ZHANG Guangliang WANG Chinese Academy of Surveying and Mapping Beijing 100830 P.R.China University of Twente PO Box 6 7500 AA Enschede The Netherlands

ISBN: (纸本)9781467314503

关键词： image Processing image and data fusion Quantitative Analysis Quality Performace Evaluation

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REGION-BASED image fusion USING A COMBINATORY CHEBYSHEV-ICA METHOD

REGION-BASED IMAGE FUSION USING A COMBINATORY CHEBYSHEV-ICA ...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Omar, Zaid Mitianoudis, Nikolaos Stathaki, Tania Imperial Coll London Commun & Signal Proc Grp Kensington SW7 2AZ England

ISBN: (纸本)9781457705397

The aim of this paper is to provide an algorithm for image fusion which combines the techniques of Chebyshev polynomial (CP) approximation and independent component analysis (ICA), based on the regional information of input images. We present a region-based method that combines the merits of both techniques. It utilises segmentation to identify edges, texture and other important features in the input image and subsequently apply the different fusion methods according to regions. The proposed method exhibits better perceptual performance than individual CP and ICA fusion approaches especially in noise corrupted images.

关键词： image and data fusion Chebyshev polynomials independent component analysis region-based fusion

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