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Typical mobile agent networks, such as multi-unmanned aerial vehicle (UAV) systems, are constrained by limited resources: energy, computing power, memory and communication bandwidth. In particular, limited energy affects system performance directly, such as system lifetime. Moreover, it has been demonstrated experimentally in the wireless sensor network literature that the total energy consumption is often dominated by the communication cost, i.e., the computational and the sensing energy are small compared to the communication energy consumption. For this reason, the lifetime of the network can be extended significantly by minimizing the communication distance as well as the amount of communication data, at the expense of increasing computational cost. In this paper, we aim at attaining an optimal tradeoff between the communication and the computational energy. Specifically, we propose a mixed-integer optimization formulation for a multihop hierarchical clustering-based self-organizing UAV network incorporating data aggregation, to obtain an energy-efficient information routing scheme. The proposed framework is tested on two applications, namely target tracking and area mapping. Based on simulation results, our method can significantly save energy compared to a baseline strategy, where there is no data aggregation and clustering scheme. [ABSTRACT FROM AUTHOR]

Networked observational devices have proliferated in recent years, contributing to voluminous data streams from a variety of sources and problem domains. These streams often have a spatiotemporal component and include multidimensional features of interest. Processing such data in an offline fashion using batch systems or data warehouses is costly from both a storage and computational standpoint, and in many situations the insights derived from the data streams are useful only if they are timely. In this study, we propose Synopsis, an online, distributed sketch that is constructed from voluminous spatiotemporal data streams. The sketch summarizes feature values and inter-feature relationships in memory to facilitate real-time query evaluations and to serve as input to computations expressed using analytical engines. As the data streams evolve, Synopsis performs targeted dynamic scaling to ensure high accuracy and effective resource utilization. We evaluate our system in the context of two real-world spatiotemporal datasets and demonstrate its efficacy in both scalability and query evaluations. [ABSTRACT FROM PUBLISHER]

Band selection is an important preprocessing step for hyperspectral data processing. It involves two crucial problems, i.e., suitable measure criterion and effective search strategy. Mutual information (MI) has been widely used as the measure criterion for its nonlinear and nonparametric characteristics. For efficient calculation, traditional MI-based criteria commonly use bivariate MI (BMI) to approximate the ideal MI-based criterion. However, these BMI-based criteria may miss the bands having discriminative information and do not give the condition of the approximation. In this paper, a novel criterion based on trivariate MI (TMI) is proposed to measure the redundancy for classification. From the multivariate MI perspective, the proposed TMI-based and traditional BMI-based criteria are proved as the low-order approximations of the ideal criterion under some assumptions. Compared with the BMI-based criteria, a more relaxed assumption condition is required for the TMI-based criterion. To alleviate the problem of few labeled samples existing in hyperspectral images, the TMI-based criterion is extended to the semisupervised TMI-based (STMI) method by adding a graph regulation term. Additionally, to search an appropriate band subset by the TMI- and STMI-based criteria, a new clonal selection algorithm (CSA) is proposed. In CSA, integer encoding and adaptive operators are devised to reduce space and time cost. Experimental results demonstrate the effectiveness of the proposed algorithms for hyperspectral band selection. [ABSTRACT FROM PUBLISHER]

Strong demands for accurate long-range 6-DOF motion sensors have been arising for the purposes of navigation and object tracking in maritime transportation. Up to now, high-end sensors such as a differential global positioning system, laser tracker, and motion-capture camera have been utilized for long-distance sensing in spite of their high cost. In this paper, we developed a long-range motion-sensing system with the combination of low-cost sensors including infrared markers, three 1-D laser sensors, and vision cameras. A proposed sensing system, referred to as the three-beam detector, can measure the 6-DOF motion of a dynamic target, even in an outdoor environment, without any prior knowledge of the initial condition of the target. Through various static and dynamic experiments, the three-beam detector is validated to have the accuracy of 3 mm at a 30-m distance. [ABSTRACT FROM PUBLISHER]

The reliability of millimeter and sub-millimeter wave radiometer measurements is dependent on the accuracy of the loads they employ as calibration targets. In the recent past on-board calibration loads have been developed for a variety of satellite remote sensing instruments. Unfortunately some of these have suffered from calibration inaccuracies which had poor thermal performance of the calibration target as the root cause. Stringent performance parameters of the calibration target such as low reflectivity, high temperature uniformity, low mass and low power consumption combined with low volumetric requirements remain a challenge for the space instrument developer. In this paper we present a novel multi-layer absorber concept for a calibration load which offers an excellent compromise between very good radiometric performance and temperature uniformity and the mass and volumetric constraints required by space-borne calibration targets. [ABSTRACT FROM AUTHOR]

A solar-powered microwave transmission system is proposed for remote sensing and communications purposes. We present in this paper a proof of concept to operate solar-powered microwave transmission and an investigation of microwave interactions with atmospheric plasmas. In this conceptualized system, a solar thermophotovoltaic system is considered to produce direct current electricity, which is then used to power solid-state microwave transmitters. The results from these simulations provide insights on how to produce an economically and environmentally conscientious energy source, which can be used for remote-sensing and communication applications. However, it is expected that microwaves may interact with ionospheric plasmas, primarily in the E-region to induce large-scale fluctuations in plasma density and geomagnetic fields with threshold wave electric-field intensities of \sim1 V/m. After we determine the instability thresholds, we can use them to set up the safe operation range of solar-powered microwave transmission. [ABSTRACT FROM PUBLISHER]

A measurement setup for imaging applications is presented. The idea is to reuse an existing antenna measurement setup to develop the imaging system by using a frequency scanning antenna array that focuses the incident field on the object under test (OUT) at different angular positions by means of a frequency sweep. From the measured total field data, an inverse technique based on source reconstruction is proposed to recover the OUT profile. In order to check the feasibility of the proposed setup and for the sake of simplicity, the OUTs to be dealt with present translation symmetry along one dimension (2-D problems). Measurement results and full-wave method-of-moment simulations are presented to test the proposed setup as well as to point out the frequency scanning capabilities. [ABSTRACT FROM PUBLISHER]

The author discusses the introduction of high-resolution remote sensing data and detectors into satellite and airborne remote sensing technologies, which is a result of advances in information processing and architectures. This synergy also manifests in applications in the fields of energy generation, water-supply management and environmental protection. Technological advances in these fields also gave rise to hyperspectral remote sensing, synthetic aperture radar (SAR) and multiangular data.

Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser imaging. These models introduce two additional layers of difficulties with respect to the standard Gaussian additive noise scenario: 1) the noise is multiplied by (rather than added to) the original image; 2) the noise is not Gaussian, with Rayleigh and Gamma being commonly used densities. These two features of multiplicative noise models preclude the direct application of most state-of-the-art algorithms, which are designed for solving unconstrained optimization problems where the objective has two terms: a quadratic data term (log-likelihood), reflecting the additive and Gaussian nature of the noise, plus a convex (possibly nonsmooth) regularizer (e.g., a total variation or wavelet-based regularizer/prior). In this paper, we address these difficulties by: 1) converting the multiplicative model into an additive one by taking logarithms, as proposed by some other authors; 2) using variable splitting to obtain an equivalent constrained problem; and 3) dealing with this optimization problem using the augmented Lagrangian framework. A set of experiments shows that the proposed method, which we name MIDAL (multiplicative image denoising by augmented Lagrangian), yields state-of-the-art results both in terms of speed and denoising performance. [ABSTRACT FROM AUTHOR]

This paper introduces a new self-calibration destriping technique for pushbroom-type satellite imaging systems. Self-calibration means that no specific training data are required. It is based on the statistical estimation of each detector gain from the observed image, assuming a linear response. Both theoretical and practical behaviors are studied. Our technique is shown to outperform simpler techniques based on column averages in terms of gain estimation precision while keeping the computational cost within admissible limits. [ABSTRACT FROM AUTHOR]

Piezoelectric transducers are increasingly being used to harvest energy from environmental vibrations in order to either power remote sensors or charge batteries that power the sensors. In this paper, a new voltage compensation scheme for high-voltage-based (> 100 V) energy harvesting is introduced, and its fundamental concepts, as well as the operation details, are elaborated. This scheme, when applied to the voltage inversion method [synchronized switch harvesting on inductor (SSHI)], provides an increase of over 14% in harvested power when com- pared to the parallel inversion method (parallel SSHI) alone and more than 50% in the case of series inversion method (series SSHI). Second, tapered cantilever beams were shown to be more effective in generating a uniform strain profile over rectangular and trapezoidal beams if they are precisely shaped, resulting in a significant increase in harvested power over available methods in the literature from laboratory experimental tests. In addition, a simplified method to design such a beam is introduced. Finally, a field test of the proposed tapered beam is conducted by using a dozer for earth-moving applications, and experimental results are discussed. [ABSTRACT FROM AUTHOR]

The implementation of a polycrystalline silicon solar cell as a microwave groundplane in a low-profile, reduced-footprint microstrip patch antenna design for autonomous communication applications is reported. The effects on the antenna/solar performances due to the integration, different electrical conductivities in the silicon layer and variation in incident light intensity are investigated. The antenna sensitivity to the orientation of the anisotropic solar cell geometry is discussed. [ABSTRACT FROM AUTHOR]

On December 12, 2006, both the European Remote Sensing Satellite 2 and Environmental Satellite recorded a high-magnitude flood event on the River Dee in Wales (U.K.) only 28 min apart. This unique opportunity enables the creation of a very rare but extremely useful observed data set for flood inundation studies. For flood management purposes, hydrodynamic models are often run after an event but with field data gauged during the event to approximate both flood area and depth. As an adequate a priori definition of model parameters is difficult, they tend to be run with multiple parameter sets to generate a likelihood of inundation map. However, as field observations of events are often very scarce, these output maps cannot be validated with field-observed probabilities. This paper illustrates how this unique set of spaceborne radar images can be used in combination with five widely used image processing techniques to generate an event-specific inundation map that expresses a degree of belief that a given pixel is possibly flooded. It is expected that the value of this multialgorithm ensemble-based map opens UP new ways to evaluate the performance of hydrodynamic models, as it contains information which has, to the authors' knowledge, not previously been available. [ABSTRACT FROM AUTHOR]

Digital image-based elasto-tomography technology relies on obtaining high-resolution images of a breasts surface under high-frequency actuation, typically in the range of 50-100 Hz. Off-the-shelf digital cameras and imaging elements are unable to capture images directly at these speeds. A method based on strobe imaging is presented for obtaining the required high-speed image capture at a resolution of 1280 × 1024 pixels and actuation frequency of 100 Hz. The final working system produced images that enabled effective 3-D motion tracking of the surface of a silicon phantom. The motion is tracked accurately using a novel Euclidean Invariant signature method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the accurate laminary determination of the thickness of coatings on metallic surfaces. The development goal was to devise a system that allows for highly spatially resolved full-frame 2-D scans that conventional systems are not able to provide. Furthermore, it is able to allow for a sufficiently large physical separation between the measuring head and the inspected surface to accommodate industrial environments that provide a high operating velocity and is able to detect quality problems of square millimeter in size. The system consists of a heat source that introduces a thermal transient to the surface layer of the specimen, a thermal imaging system to acquire the time-dependent cooling behavior, and an image processing system to determine thermal parameters indicative of surface quality and/or coating thickness. The results clearly show that a thickness resolution of better than 50 μm can reliably be obtained at a scanning velocity of 0.37 m/s, covering a field of view (FOV) of approximately 200 × 140 mm². [ABSTRACT FROM AUTHOR]

The mosaicking of orthoimages has been used to cover a large geographic region for various applications ranging from environmental monitoring to disaster management. How- ever, existing mosaicking methods mainly focus on the generation of seamlines between two adjacent orthoimages. In this paper, we present a novel approach based on the use of a seamline network formed by a novel area Voronoi diagrams with overlap and the use of effective mosaic polygons (EMPs) to define the pixels of each orthoimage for the final mosaic. The generated seamline network is global based and is also optimized after refinement. It gives an effective partitioning for the regions of all orthoimages to form EMPs. The partitioning is unique, seamless, and has no redundancy. The algorithm is parallel, and the EMP of each orthoimage only has relation to orthoimages which have overlaps with it. It can ensure the flexibility and efficiency of mosaicking, without an intermediate process and independent of the sequence of the image composite. The experimental results obtained from the mosaicking of 40 color orthoimages demonstrate considerable potential for generating a seamline network automatically and effectively. This is extremely useful when a seamless mosaic is required to cover a large geographic region. [ABSTRACT FROM AUTHOR]

In this paper, we explore using the ultrawide-band radar technology for sensing through-the-wall imaging. We conducted a field experiment with our in-house designed impulse-based radar, in which a stripmap synthetic aperture radar (SAR) geometry was employed in mapping an abandoned Army barrack building with a large footprint area. The images obtained from two sides of the building were combined in order to obtain the full building layout, including the interior structure. Computer simulations performed with Xpatch, a physical optics-based ray tracing code, are used to explain some phenomena observed in the measured SAR images. [ABSTRACT FROM AUTHOR]

A novel microwave imaging method to detect and possibly characterize nonaccessible targets concealed into a wall or a floor from the measured backscattered field is proposed. The problem is cast as an inverse scattering one aimed at imaging a piecewise homogeneous target embedded in a layered structure. The proposed method is based on a linear sampling method (LSM), a general and computationally effective shape-reconstruction approach that determines the targets morphology through an indicator defined as the regularized solution of a linear inverse problem. However, LSM cannot discern between homogeneous and inhomogeneous targets; hence, it may retrieve the cache but not characterize its content. To overcome this drawback, we propose a two-step approach in which the cache is first imaged by using the standard LSM indicator. Then, by taking advantage of the physical interpretation of the LSM and of the first step's result, a modified indicator is defined and exploited to detect the inclusions possibly hidden in the retrieved cache. Numerical examples are provided as a proof of concept. [ABSTRACT FROM AUTHOR]

Terrestrial And Planetary Imaging Radar (TAPIR) is an innovative high-frequency ground-penetrating radar (GPR) developed in the frame of the Martian NetLander mission to probe the subsurface down to kilometric depths. Unlike most GPRs, TAPIR is able to image underground reflectors with stationary antennas. In this paper, after a brief presentation of the instrument, we describe the method developed to interpret data collected during the RAdar of NEtlander in Terre Adélie (RANETA) field survey in Antarctica. This method consists of retrieving the direction of arrival of each detected echo through the measurement of five components of the electromagnetic field (the three magnetic components and the horizontal components of the electric field). Thus, both the range and the direction of each individual reflection or diffraction due to the ice-bedrock interface are resolved. We validated this method on finite-difference time-domain numerically simulated data for different subsurface configurations before applying it to RANETA observations. In particular, the irregular topography of the bedrock in two sounding sites was revealed. We discuss the accuracy of our results. [ABSTRACT FROM AUTHOR]

When separating objects from a background in an image, we often meet difficulties in obtaining the precise output due to the unclear edges of the objects, as well as the poor or nonuniform illumination. In order to solve this problem, this paper presents an in situ segmentation method that takes advantage of the distribution feature of illumination of light sources, rather than analyzing the image pixels themselves. After analyzing the convexity of illumination distribution (CID) of point and linear light sources, the paper makes use of the CID features to find pixels belonging to the background. Then, some background pixels are selected as control points to reconstruct the image background by means of B-spline; finally, by subtracting the reconstructed background from the original image, global thresholding can be employed to make the final segmentation. Quantitative evaluation experiments are made to test the performance of the method. [ABSTRACT FROM AUTHOR]

In this paper, the preliminary design and assessment of a high-resolution 3-D acoustic imaging system based on a sparse planar array of sensors, which is particularly intended for underwater applications, are presented. Critical issues in the development of high-resolution 3-D sonar systems are 1) the cost of hardware, which is associated with the huge number of sensors that compose the planar array, and 2) the computational burden of processing the signals that were gathered. Here, such problems are overcome by the optimized synthesis of an aperiodic sparse array that allows the device to operate at different frequencies, yielding an acceptable sidelobe level and a good tradeoff between the field of view and the resolution. The array optimization is performed using an efficient stochastic method, in which the number of sensors is minimized, whereas their positions and weights are simultaneously optimized. To test the validity of the designed system, the signals that the sparse array received in response to the insonification of a scene with a wideband pulse are simulated, and voxel-based beamforming is applied to generate the 3-D image. The obtained images show high fidelity to the geometrical characteristics of the scene, in accordance with the expected performance of the 3-D sonar system. [ABSTRACT FROM AUTHOR]

The increasing quantity and sophistication of imaging spectroscopy applications have led to a higher demand on the quality of Earth observation data products. In particular, it is desired that data products be as consistent as possible (i.e., ideally uniform) in both spectral and spatial dimensions. Yet, data acquired from real (e.g., pushbroom) imaging spectrometers are adversely affected by various categories of artifacts and aberrations including as follows: singular and linear (e.g., bad pixels and missing lines), area (e.g., optical aberrations), and stability and degradation defects. Typically, the consumer of such data products is not aware of the magnitude of such inherent data uncertainties even as more uncertainty is introduced during higher level processing for any particular application. In this paper, it is shown that the impact of imaging spectrometry data product imperfections in currently available data products has an inherent uncertainty of 10%, even though worst case scenarios were excluded, state-of-the-art corrections were applied, and radiometric calibration uncertainties were excluded. Thereafter, it is demonstrated how this error can be reduced (< 5%) with appropriate available technology (onboard, scene, and laboratory calibration) and assimilation procedures during the preprocessing of the data. As a result, more accurate, i.e., uniform, imaging spectrometry data can be delivered to the user community. Hence, the term uniformity of imaging spectrometry data products is defined for enabling the quantitative means to assess the quality of imaging spectrometry data. It is argued that such rigor is necessary for calculating the error propagation of respective higher level processing results and products. [ABSTRACT FROM AUTHOR]

With the synthetic aperture radar (SAR) sensor PALSAR onboard the Advanced Land Observing Satellite, a new full-polarimetric spaceborne L-band SAR instrument has been launched into orbit. At L-band, Faraday rotation (FR) can reach significant values, degrading the quality of the received SAR data. One-way rotations exceeding 25° are likely to happen during the lifetime of PALSAR, which will significantly reduce the accuracy of geophysical parameter recovery if uncorrected. Therefore, the estimation and correction of FR effects is a prerequisite for data quality and continuity. In this paper, methods for estimating FR are presented and analyzed. The first unambiguous detection of FR in SAR data is presented. A set of real data examples indicates the quality and sensitivity of FR estimation from PALSAR data, allowing the measurement of FR with high precision in areas where such measurements were previously inaccessible. In examples, we present the detection of kilometer-scale ionospheric disturbances, a spatial scale that is not detectable by ground-based GPS measurements. An FR prediction method is presented and validated. Approaches to correct for the estimated FR effects are applied, and their effectiveness is tested on real data. [ABSTRACT FROM AUTHOR]

Microwave radiometers detecting geophysical parameters are very susceptible to radio-frequency interference (RFI) from anthropogenic sources. RFI is always additive to a brightness observation, and so the presence of RFI can bias geophysical parameter retrieval. As microwave radiometers typically have the most sensitive receivers operating in their band, low-level RFI is both significant and difficult to identify. The kurtosis statistic can be a powerful means of identifying some types of low-level RFI, as thermal noise has a distinct kurtosis value of three, whereas thermal noise contaminated even with low-level nonthermal RFI often has other values of kurtosis. This paper derives some benign distortions of the kurtosis statistic due to digitization effects and demonstrates these effects with a laboratory experiment in which a known amount of low-level RFI is injected into a digital microwave radiometer. [ABSTRACT FROM AUTHOR]

This paper develops mathematical techniques and makes use of interferometric synthetic aperture radar (InSAR) for improving the quality of digital elevation models derived from SAR images and providing accurate estimations of atmospheric path and absolute phase delays and water vapor content estimation. The problem of solving parameters such as atmospheric path delay, height, and unwrapping errors is to be described in a mathematical form that uses QR factorization techniques for solving rank-deficient systems. A new approach for the solution of rank-deficient systems with few independent equations is proposed. In the new approach, the bounds are considered known and provided by the eigenvalues. New eigenvalues are added inside the bounds. During the implementation, attention is given not to exceed the bounds of the reorganized matrix. This approach is the first time that is used for phase parameterization in terms of height, tropospheric delay, and phase unwrapping errors. Expanding the approach was also studied for absolute phase delay and water vapor content estimation. The investigation and the implementation of the approach make use of ENVISAT images. The validation of results was implemented through GPS and meteorological measurements. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the mapping between the 3-D scene space and the bistatic synthetic aperture radar (SAR) image space and show that when the direction of the angular velocity of the bistatic SAR remains constant, the process of bistatic SAR imaging can be approximately modeled as a perspective operator from the 3-D scene space to the 2-D image space, and the perspective line is perpendicular to the plane determined by the composition direction of the T/R line of sight and the composition direction of the angular velocity of the T/R platform. Then, we show that the 2-D point spread function of the bistatic SAR is determined not only by the range and "azimuth" resolutions but also by the geometry of the bistatic SAR and the bases of the SAR image space, and the concept "ambiguity region" is introduced to describe the ambiguity problem in the 3-D scene space. Then, the range-Doppler algorithm is discussed, and a new translational-variant bistatic SAR imaging method is proposed, which uses the scaled inverse fast Fourier transform (IFFT) technique to eliminate the translational-variant feature of the SAR space resolution. The space truncation error of this new algorithm is discussed to analyze the depth of focus of the scaled IFFT bistatic SAR imaging algorithms, and we find that the upper bounce of the space truncation error is proportional to the square of the distance from the scatterer to the T/R platforms. Last, the effects of motion measurement errors are discussed in detail, and, through theoretical analysis and numerical experiments, we show that the absolute position measurement error, the baseline measurement error, the perpendicular (vertical) component of the absolute velocity measurement error (AVME), and the perpendicular component of the relative velocity measurement error (RVME) cause SAR image shifting in the image space mainly, and the parallel component of the AVME and the parallel component of the RVME cause the SAR image to severely defocus. [ABSTRACT FROM AUTHOR]

In this paper, a new and improved L-band version of the correlated noise calibration standard (CNCS) has been developed to aid in the characterization of polarimetric microwave radiometers. The CNCS generates a series of known polarimetric test signals using a two-channel commercial arbitrary waveform generator (AWG) and a pair of frequency-upconversion modules. When it is inserted in place of the antenna used by a radiometer-under-test (RUT), it can fully characterize the polarimetric response of the receiver portion of the RUT. Both hardware and software improvements have been made over a previous version of the CNCS. The frequency upconverters now include integral warm and cold calibration-reference targets to automatically compensate for small drifts in AWG output-signal strength. The procedure used to calibrate the RUT has been generalized to correct for nonideal characteristics of the CNCS itself. Moreover, the effects on the derived polarimetric gain matrix of impedance mismatches between the RUT, and either the CNCS or the antenna have been determined. Details of the CNCS improvements are presented. The results of an experimental demonstration of its use and of a series of validation tests of its performance are also presented. [ABSTRACT FROM AUTHOR]

In recent years, the use of radar technology has been proposed in a wide range of subsurface imaging applications. Traditionally, linear scan trajectories are used to acquire data in most subsurface radar applications. However, novel applications, such as breast microwave imaging and wood inspection, require the use of nonlinear scan trajectories in order to adjust to the geometry of the scanned area. This paper proposes a novel reconstruction algorithm for subsurface radar data acquired along cylindrical scan trajectories. The spectrum of the collected data is processed in order to locate the spatial origin of the target reflections and remove the spreading of the target reflections which results from the different signal travel times along the scan trajectory. The proposed algorithm was successfully tested using experimental data collected from phantoms that mimic high contrast subsurface radar scenarios, yielding promising results. Practical considerations such as spatial resolution and sampling constraints are discussed and illustrated as well. [ABSTRACT FROM AUTHOR]

This paper considers the problem of high-dynamic-range (HDR) image capture using low-dynamic-range (LDR) cameras. We present three different minimal-bracketing algorithms for computing minimum-sized exposure sets bracketing of HDR scenes. Each algorithm is applicable to a different HDR-imaging scenario depending on the amount of target-scene-irradiance information and real-time image processing available at the time of image acquisition. We prove the optimality of each algorithm with respect to its ability to obtain a theoretically minimum-size bracketing set of exposures. We also provide closed-form expressions for computing minimal-bracketing exposure sets for two common types of HDR-imaging systems, those with geometrically varying and arithmetically varying exposure settings. We experimentally demonstrate the advantages of the proposed methods by capturing and processing multiple HDR scenes using minimal-bracketing and 1-stop bracketing methods. The results show that minimal-bracketing can be used to produce high-quality HDR images, while requiring only one third as many LDR images be acquired compared to 1-stop bracketing. We also perform a detailed SNR analysis that quantifies the tradeoff between signal-to-noise ratio and image-bracketing-set size. [ABSTRACT FROM AUTHOR]

Super-resolution (SR) techniques produce a high-resolution image from a set of low-resolution undersampled images. In this paper, we propose a new method for super-resolution that uses sampling theory concepts to derive a noniterative SR algorithm. We first raise the issue of the validity of the data model usually assumed in SR, pointing out that it imposes a band-limited reconstructed image plus a certain type of noise. We propose a sampling theory framework with a prefiltering step that allows us to work with more general data models and also a specific new method for SR that uses Delaunay triangulation and B-splines to build the super-resolved image. The proposed method is noniterative and well posed. We prove its effectiveness against traditional iterative and noniterative SR methods on synthetic and real data. Additionally, we also prove that we can first solve the interpolation problem and then make the deblurring not only when the motion is translational but also when there are rotations and shifts and the imaging system Point Spread Function (PSF) is rotationally symmetric. [ABSTRACT FROM AUTHOR]

In this paper, a novel despeckling algorithm based on undecimated wavelet decomposition and maximum a posteriori estimation is proposed. Such a method represents an improvement with respect to the filter presented by the authors, and it is based on the same conjecture that the probability density functions (pdfs) of the wavelet coefficients follow a generalized Gaussian (GG) distribution. However, the approach introduced here presents two major novelties: 1) theoretically exact expressions for the estimation of the GG parameters are derived: such expressions do not require further assumptions other than the multiplicative model with uncorrelated speckle, and hold also in the case of a strongly correlated reflectivity; 2) a model for the classification of the wavelet coefficients according to their texture energy is introduced. This model allows us to classify the wavelet coefficients into classes having different degrees of heterogeneity, so that ad hoc estimation approaches can be devised for the different sets of coefficients. Three different implementations, characterized by different approaches for incorporating into the filtering procedure the information deriving from the segmentation of the wavelet coefficients, are proposed. Experimental results, carried out on both artificially speckled images and true synthetic aperture radar images, demonstrate that the proposed filtering approach outperforms the previous filters, irrespective of the features of the underlying reflectivity. [ABSTRACT FROM AUTHOR]

We review the algorithms that have been used to discriminate between hazardous unexploded ordnance (UXO) and harmless clutter. Statistical classifiers use model parameters estimated from geophysical data to formulate a decision rule. This rule tries to discriminate between UXO and clutter using the available information. In contrast, library-based discrimination algorithms make decisions using a predefined library of signatures for expected UXO types. Given the variety of algorithms that are available for UXO discrimination, we describe two metrics for evaluating discrimination performance—the area under the receiver operating characteristic and the false-alarm rate. We propose a bootstrapping algorithm for estimating these metrics when limited data are available. Last, we demonstrate this approach on real electromagnetic and magnetic data sets. [ABSTRACT FROM AUTHOR]

Employing the 3-D mapping and projection algorithm (MPA), an imaging simulation of bistatic synthetic aperture radar (BISAR) observation over a complex scenario is developed. Based on the explicit expression of the point target response of stripmap BISAR imaging, raw data are efficiently generated from the scattering map precalculated by MPA. Some examples of BISAR image simulation are studied. The polarimetric characteristics of a BISAR image are then discussed. It is found that some typical polarimetric parameters such as Cloude's α, β, and γ might become unable to describe the scattering mechanism under bistatic observation. A transform of unified bistatic polar bases for a BISAR image is proposed. The parameters α, β, and γ are modified to retain the property of orientation independence in the bistatic circumstance. Analysis of simulated images shows that the redefined α, β, and γ after the unified bistatic polar bases transform well describe different scattering mechanisms in BISAR imaging. It provides a primary tool for BISAR image interpretation and terrain classification. [ABSTRACT FROM AUTHOR]

This paper derives a 2-D spectrum model for general bistatic synthetic aperture radar (SAR). By introducing some new parameters such as equivalent monostatic parameters, bistatic factor, and weighted-equivalent range, the 2-D spectrum of general bistatic. SAR can be expressed in the form of monostatic SAR even when the transmitter and receiver move along unparallel trajectories with different velocities. The result formulates bistatic SAR into an equivalent monostatic SAR model and would be useful for developing efficient bistatic SAR algorithms in frequency-domain or hybrid-domain processing. Simulation results are given to validate the performance of the model. For special bistatic SAR configurations, the model can be simplified. Compared to other similar models, the proposed model is clearer and much more concise. [ABSTRACT FROM AUTHOR]

C- and L-band airborne synthetic aperture radar (SAR) imagery acquired at like- and cross-polarizations over sea ice under winter conditions is examined with the objective to study the discrimination between level ice and ice deformation features. High-resolution low-noise data were analyzed in the first paper. In this second paper, the main topics are the effects of spatial resolution and signal-to-noise ratio. Airborne high-resolution SAR scenes are used to generate a sequence of images with increasingly coarser spatial resolution from 5 to 25 m, keeping the number of looks constant. The signal-to-noise ratio is varied between typical noise levels for airborne imagery and satellite data. Areal fraction of deformed ice and average deformation distance are determined for each image product. At L-band, the retrieved values of the areal fraction get larger as the image resolution is degraded. The areal fraction at C-band remains constant. The retrieved average distance between deformation features increases both at C- and L-bands as the image resolution gets coarser. The influence of noise becomes noticeable if its level is equal or larger than the average intensity backscattered from the level ice. The retrieval of deformation parameters using simulated images that resemble ERS-2 SAR, Envisat ASAR, and ALOS PALSAR data products is discussed. Basic differences between real and simulated ERS-2 SAR images are analyzed. [ABSTRACT FROM AUTHOR]

Sparse signal representations and approximations from overcomplete dictionaries have become an invaluable tool recently. In this paper, we develop a new, heuristic, graph-structured, sparse signal representation algorithm for overcomplete dictionaries that can be decomposed into subdictionaries and whose dictionary elements can be arranged in a hierarchy. Around this algorithm, we construct a methodology for advanced image formation in wide-angle synthetic aperture radar (SAR), defining an approach for joint anisotropy characterization and image formation. Additionally, we develop a coordinate descent method for jointly optimizing a parameterized dictionary and recovering a sparse representation using that dictionary. The motivation is to characterize a phenomenon in wide-angle SAR that has not been given much attention before: migratory scattering centers, i.e., scatterers whose apparent spatial location depends on aspect angle. Finally, we address the topic of recovering solutions that are sparse in more than one objective domain by introducing a suitable sparsifying cost function. We encode geometric objectives into SAR image formation through sparsity in two domains, including the normal parameter space of the Hough transform. [ABSTRACT FROM AUTHOR]

InAs/AlSb/GaSb backward diodes are used for millimeter-wave square-law power detection. A new heterostructure design with low capacitance, low resistance, and high curvature coefficient as compared to previous designs is presented. Voltage sensitivity, which is directly proportional to curvature coefficient, is improved by 31% as compared to prior reports of devices with similar barrier thicknesses. The junction capacitance is also reduced by 24% to 13 fF/μm2. The improved sensitivity and decreased junction capacitance originate from the incorporation of a p-type δ-doping plane with sheet concentration of 1 × 1012 cm-2 in the n-InAs cathode layer. The combination of low resistance (and thus Johnson noise) and high sensitivity results in an estimated noise equivalent power of 0.24 pW/Hz½ at 94 GHz for a conjugately matched source, whereas the reduced capacitance facilitates wideband matching and increases the detector cutoff frequency. These modified Sb-based detectors have promise for improving the performance of passive millimeter-wave and submillimeter-wave imaging systems. [ABSTRACT FROM AUTHOR]

This paper presents an integrated color imaging system for taking images in extremely high dynamic range scenes. The system first fuses several differently exposed raw images to acquire more intensity information. The effective dynamic range of the image raw data can be extended to 256 times ~five differently exposed images are fused. Then it runs edge detection iterations to extract the image details in different luminance levels. The proposed tone reproduction algorithm equalizes the histogram of the extracted fine edges which tends to assign larger dynamic range for highly populated regions. Finally, the local contrast enhancement is performed to further refine the image details. The experimental results show that the proposed high dynamic range imaging system has good performance on both tone and color reproduction'. [ABSTRACT FROM AUTHOR]

Consensual and hierarchical approaches are developed for the classification of remotely sensed multispectral images. The proposed method consists of preprocessing of input patterns, generating multiple classification results by hierarchical neural networks, and a combining scheme to generate a consensus of multiple classification results. Transformations of input patterns by random matrices and nonlinear filtering are used for preprocessing. By varying the input patterns, the multiple classification results are generated with sufficiently independent errors by using a single type of classifier. This helps to improve classification performance when the multiple classification results are combined. Hierarchical neural networks involve the use of successive classifiers which are tuned to reduce the remaining errors to increase the classification performance. This structure includes detection schemes to decide whether successive classifiers are utilized for each input. Consensual and hierarchical approaches generate more reliable and accurate results based on group decision. [ABSTRACT FROM AUTHOR]

High-performance models are required during the design (phase) of sensing devices in order to take their physical behavior into account and to include these models in calculations and simulations aimed at optimizing the performance of devices in fixed operating conditions. In this paper, the problem of model fitting for ferroelectric devices is addressed; in particular, a model of the behavior of a ferroelectric capacitor is accomplished. The static behavior of such devices is investigated, and an experimental setup for both characterization and model estimation is proposed. The model obtained is assessed, and the uncertainty introduced by the measurement system is estimated. [ABSTRACT FROM AUTHOR]

This paper aims at demonstrating the possibility of merging data from various medium-resolution spaceborne sensors to produce a consistent time series of surface bidirectional reflectance distribution function (BRDF) and albedo products. The spectral, directional, temporal, and spatial aspects of the multisensor fusion are presented. Emphasis is then given on the spectral normalization for the fusion of Medium Resolution Imaging Spectrometer Instrument (MERIS) data with Moder- ate Resolution Imaging Spectroradiometer (MODIS) and VEGETATION (VGT) data. Two methods are evaluated: a simple statistical method, which relies on a linear regression using all the available spectral bands, and a more innovative method called the spectral mode method, which is based on the restitution of the surface spectral signature by a combination of universal spectral functions. Analysis with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data and satellite products reveals that the spectral mode method is more efficient. This approach is used to merge top-of-canopy bidirectional reflectances from MERIS and VGT for the restitution of BRDF and albedo over a subset of West Africa. Compared to the products obtained with MERIS alone, the fusion with VGT demonstrates an improvement of the spatial coverage and a reduction of product uncertainty by about a third. [ABSTRACT FROM AUTHOR]

In through-the-wall imaging, errors in wall parameters cause targets to be imaged away from their true positions. The displacement in target locations depend on the accuracy of the estimates of the wall parameters as well as the target position relative to the antenna array. A technique using two or more standoff distances of the imaging system from the wall is proposed for application Leader wall parameter ambiguities. Two different imaging schemes can then be applied to correct for errors in wall characteristics. The first scheme relies on forming target displacement trajectories, each corresponding to a different standoff distance, and assuming different values of wall thickness and dielectric constant. The target position is then determined as the trajectories crossover point. In the second scheme, an image sequence is generated. Each specific image in this sequence is obtained by summing those corresponding to different standoff distances, but with the same assumed wall parameters. An imaging-focusing metric can then be adopted to determine the target position. The paper analyzes the above two schemes and provides extensive simulation examples demonstrating their effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we present a methodology to design filters for an imaging system to improve the accuracy of the spectral measurements for families of reflective surfaces. We derive the necessary and sufficient conditions that the sensor space of the system must obey in order to measure the spectral reflectance of the sur- faces accurately. Through simulations, we show how these conditions can be applied to design filters using a set of sample spectral data acquired from extracted teeth. For this set of data, we also compare our results to those of Wolski's method [1], a conventional filter design method which produces filters that recover tristimulus values of surfaces accurately under several illuminants. We show that our method produces filters that capture the spectral reflectance better given the same number of measurements. The errors in predicting the color of the sample data are much lower under every test illuminant when the filters designed with our method are used. [ABSTRACT FROM AUTHOR]

Three dimensional (3-D) imaging and display have been subjects of much research due to their diverse benefits and applications. However, due to the necessity to capture, record, process, and display an enormous amount of optical data for producing high-quality 3-D images, the developed 3-D imaging techniques were forced to compromise their performances (e.g., gave up the continuous parallax restricting to a fixed viewing point) or to use special devices and technology (such as coherent illuminations, special spectacles) which is inconvenient for most practical implementation. Today's rapid progress of digital capture and display technology opened the possibility to proceed toward noncompromising, easy-to-use 3-D imaging techniques. This technology progress prompted the revival of the integral imaging (II) technique based on a technique proposed almost one century ago. II is a type of multiview 3-D imaging system that uses an array of diffractive or refractive elements to capture the 3-D optical data. It has attracted great attention recently, since it produces autostereoscopic images without special illumination requirements. However, with a conventional II system it is not possible to produce 3-D images that have both high resolution, large depth-of-field, and large viewing angle. This paper provides an overview of the approaches and techniques developed during the lost decade to overcome these limitations. By combining these techniques with upcoming technology it is to be expected that II-bused 3-D imaging systems will reach practical applicability in various fields. [ABSTRACT FROM AUTHOR]

A novel contact opening mechanism has been developed using a piezoelectric actuator to open the contacts in a low contact opening velocity circuit breaker. The arc control on the contacts is critical for successful current interruption (10³ - 10´ A) in low voltage (<250 V) devices. Previous work has shown how arc root commutation from the contact region into the arc chamber is affected by arc chamber materials, contact materials and the gap behind the moving contact for contact velocities between 1 ms-1 and 10 ms-1. This work is extended using a commercially available piezoelectric actuator to open the contacts. Contact opening speeds are assessed and the arc root mobility is characterized under this operating regime. A flexible test apparatus and solid-state high-speed arc imaging system are used to gather data on the arc root during the opening of the contacts. New experimental results are presented on the anode and cathode root velocity and arc root motion in an arc chamber with piezoelectrically actuated contact opening. These results can be used to improve the design of high current low voltage circuit breakers suitable for piezoelectric actuation. [ABSTRACT FROM AUTHOR]

The automatic segmentation of nuclei in confocal reflectance images of cervical tissue is an important goal toward developing less expensive cervical precancer detection methods. Since in vivo confocal reflectance microscopy is an emerging technology for cancer detection, no prior work has been reported on the automatic segmentation of in vivo confocal reflectance images. However, prior work has shown that nuclear size and nuclear-to-cytoplasmic ratio can determine the presence or extent of cervical precancer. Thus, segmenting nuclei in confocal images will aid in cervical precancer detection. Successful segmentation of images of any type can be significantly enhanced by the introduction of accurate image models. To enable a deeper understanding of confocal reflectance microscopy images of cervical tissue, and to supply a basis for parameter selection in a classification algorithm, we have developed a model that accounts for the properties of the imaging system and of the tissues. Using our model in conjunction with a powerful image enhancement tool (anisotropic median-diffusion), appropriate statistical image modeling of spatial interactions (Gaussian Markov random fields), and a Bayesian framework for classification-segmentation, we have developed an effective algorithm for automatically segmenting nuclei in confocal images of cervical tissue. We have applied our algorithm to an extensive set of cervical images and have found that it detects 90% of hand-segmented nuclei with an average of 6 false positives per frame. [ABSTRACT FROM AUTHOR]

The design and testing of a beam-scanning pillbox antenna for use in a 200 GHz imaging system is presented. The antenna features a rotating subreflector that scans the antenna's fan beam and a multimode structure that reduces ohmic loss and allows use of two orthogonal polarizations. The antenna has an aperture size of 450 × 5 mm, half-power beam widths of approximately 0.4° and 18° and a beam-scan range of 10°. The gain of the antenna was measured to be greater than 33 dBi for both polarizations. The radiation patterns of the pillbox antenna have been measured in the radiating near field using an outdoor range. Good agreement between measured and calculated patterns has been obtained. [ABSTRACT FROM AUTHOR]

The detective quantum efficiency (DQE) is generally accepted as the primary metric of signal-to-noise performance in medical X-ray imaging systems. Simple theoretical models of the Wiener noise power spectrum (NPS) and DQE can be developed using a cascaded-systems approach to assess particular system designs and establish operational benchmarks. However, the cascaded approach is often impractical for the development of comprehensive models due to the complexity and extremely large number of algebraic terms that must be manipulated to describe signal and noise transfer. We have developed a computational engine that overcomes this limitation. Using a predefined library of elementary physical processes, complex models are assembled and input-output relationships established using a graphical interface. A novel recursive algorithm is described that allows the signal and noise analyses of models with arbitrary complexity including the use of multiple parallel cascades. Symbolic mathematics is used to develop analytic expressions for the NPS and DQE. The algorithm is validated by manual calculation for simple models and by Monte Carlo calculation for complex models. We believe our approach enables the use of complex cascaded models to design better detectors with improved image quality. [ABSTRACT FROM AUTHOR]

We consider polarimetric images formed with coherent waves, such as in laser-illuminated imagery or synthetic aperture radar. A definition of the contrast between regions with different polarimetric properties in such images is proposed, and it is shown that the performances of maximum likelihood-based detection and segmentation algorithms are bijective functions of this contrast parameter. This makes it possible to characterize the performance of such algorithms by simply specifying the value of the contrast parameter. [ABSTRACT FROM AUTHOR]

The plane-wave scattering matrix is used to characterize antennas that are located just above a planar interface that separates two media. The plane-wave transmitting spectrum for the field radiated downward into the lower medium is expressed directly in terms of the current distribution of the transmitting antenna. The transmitting spectrum for a reciprocal antenna determines the plane-wave receiving spectrum for the field that propagates upward in the lower medium. A measurement procedure is discussed for determining the plane-wave transmitting and receiving spectra from measurements with a probe that is located in the lower medium. [ABSTRACT FROM AUTHOR]