Titlebook: Computer Vision Beyond the Visible Spectrum; Bir Bhanu (Fellow IEEE, AAAS, IAPR, Senior Honeywe Book 2005 Springer-Verlag London 2005 3D.A

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2191-6586 ge processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.978-1-84996-887-4978-1-84628-065-8Series ISSN 2191-6586 Series E-ISSN 2191-6594

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Methods for Improving the Performance of an SAR Recognition System,R) imagery under the extended operating conditions of object articulation, occlusion, and configuration variants. The fundamental approach uses recognition models based on quasi-invariant local features, radar scattering center locations, and magnitudes. Three basic extensions to this approach are d

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Target Classification Using Adaptive Feature Extraction and Subspace Projection for Hyperspectral Iobtained through a large number of narrow contiguous spectral channels (often over a hundred). Targets are man-made objects (e.g., vehicles) whose constituent materials and internal structures are usually substantially different from natural objects (i.e., backgrounds). The basic premise of hyperspe

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Face Recognition in the Thermal Infrared,video cameras sense reflected light, thermal infrared cameras primarily measure emitted radiation from objects such as faces. Visible and thermal infrared image data collections of frontal faces have been on-going at NIST for over two years, producing the most comprehensive face database known to in

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Visualization and Segmentation Techniques in 3D Ultrasound Images,accurate and quantitative monitoring of disease progression or regression. 2D viewing of 3D anatomy, using conventional ultrasonography limits our ability to quantify and visualize pathology and is partly responsible for the reported variability in diagnosis and monitoring of disease progression. Ef