Advanced sciences and technologies for security applications ;
v. 3
Includes bibliographical references and index.
Kernel-Based Nonlinear Subspace Target Detection for Hyperspectral Imagery -- Theory of Invariant Algebra and Its Use in Automatic Target Recognition -- Automatic Recognition of Underground Targets Using Time-Frequency Analysis and Optimization Techniques -- A Weighted Zak Transform, Its Properties, and Applications to Signal Processing -- Using Polarization Features of Visible Light for Automatic Landmine Detection -- The Physics of Polarization-Sensitive Optical Imaging -- Dispersion, Its Effects, and Compensation -- Multisensor Target Recognition in Image Response Space Using Evolutionary Algorithms -- Biophysics of the Eye in Computer Vision: Methods and Advanced Technologies -- Two Approaches to 3D Microorganism Recognition Using Single Exposure Online (SEOL) Digital Holography -- Distortion-Tolerant 3D Object Recognition by Using Single Exposure On-Axis Digital Holography -- Design of Distortion-Invariant Optical ID Tags for Remote Identification and Verification of Objects -- Speckle Elimination With a Maximum Likelihood Estimation and an Isoline Regularization.
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Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filter. The issue of invariants of sensor and transmission transformations (geometrical, spectral and polarimetric invariants) will be explored. These invariants are crucial in the development of low latency and computationally manageable ATR systems. The book addresses the issue of transformations that a signal goes through in its interactions with targets and background, in its passage through a medium and its final reception by a sensor. Only through understands of these transformations one can hope in addressing the inverse problem: the identification of originating sources of a signal (target recognition). The book presents recent advances from internationally known leaders of industry, government, and academia in the field of optical and photonic sensors, systems and devices for sensing, imaging, detection, identification, recognition, prevention, verification and authentication.