Calibration Information Research Articles

Historical Photograph Orthorectification Using SfM for Land Cover Change Analysis

Historical photographs acquired early 1900s provide valuable baseline data for earth surface change analysis. However, orthorectifying such data faces great challenges due to relatively low radiometric quality, the difficulty in finding control points due to surface changes, and the lack of camera calibration information. This study developed a method to standardize the scanned photographs into a common camera model, and a workflow to perform block bundle adjustment in aerial triangulation using the structure from motion technology that calibrates cameras within the aerial triangulation solution. Orthophotograph and DSM were generated from the historical photographs. This could potentially push the quantitative analysis of land surface change several decades back before the modern remote sensing era. The stability of aerial triangulation solutions using structure from motion and the accuracy of the produced DSM and orthophotographs were evaluated.

Combining Biomarker Calibration Data to Reduce Measurement Error.

Biomarker assay measurement often consists of a two-stage process where laboratory equipment yields a relative measure which is subsequently transformed to the unit of interest using a calibration curve. The calibration curve establishes the relation between the measured relative units and sample biomarker concentrations using stepped samples of known biomarker concentrations. Samples from epidemiologic studies are often measured in multiple batches or plates, each with independent calibration experiments. Collapsing calibration information across batches before statistical analysis has been shown to reduce measurement error and improves estimation. Additionally, collapsing in practice can also create an additional layer of quality control (QC) and optimization in a part of the laboratory measurement process that is often highly automated. Principled recalibration is demonstrated via. a three-step process of identifying batches where recalibration might be beneficial, forming a collapsed calibration curve and recalibrating identified batches, and using QC data to assess the appropriateness of recalibration. Here, we use inhibin B measured in biospecimens from the BioCycle study using 50 enzyme-linked immunosorbent assay (ELISA) batches (3875 samples) to motivate and display the benefits of collapsing calibration experiments, such as detecting and overcoming faulty calibration experiments, and thus improving assay coefficients of variation from reducing unwanted measurement error variability. Differences in the analysis of inhibin B by testosterone quartile are also demonstrated before and after recalibration. These simple and practical procedures are minor adjustments implemented by study personnel without altering laboratory protocols which could have positive estimation and cost-saving implications especially for population-based studies.

MPS-Net: Learning to recover surface normal for multispectral photometric stereo

Multispectral Photometric Stereo (MPS) estimates per-pixel surface normals from one single image captured under three colored (red, green and blue) light sources. Unlike traditional Photometric Stereo, MPS can therefore be used in dynamic scenes for single frame reconstruction. However, MPS is challenging due to the tangle of the illumination, surface reflectance and camera response, causing inaccurate estimation of surface normal. Existing approaches rely on either extra depth information or materials calibration strategies, thus limiting its usage in practical applications. In this paper, we propose a Multispectral Photometric Stereo Network (MPS-Net) to solve this under-determined system. The MPS-Net takes the single multispectral image and an initial surface normal estimation obtained from this image itself, and outputs an accurate surface normal map, where no extra depth or materials calibration information is required. We show that the MPS-Net is not constrained to Lambertian surfaces and can be applied to surfaces with complex reflectance. We evaluated the MPS-Net using both synthetic and real objects of various materials. Our experiment results show that the MPS-Net outperforms the state-of-the-art approaches.

Combinatorial Tuning of Structural and Optoelectronic Properties in CuxZn1−xS

Summary P-type transparent conductors (TCs) are important enabling materials for optoelectronics and photovoltaics, but their performance still lags behind n-type counterparts. Recently, semiconductor CuxZn1−xS has demonstrated potential as a p-type TC, but it remains unclear how properties vary with composition. Here, we investigate CuxZn1−xS across the entire alloy space (0 ≤ x ≤ 1) using combinatorial sputtering and high-throughput characterization. First, we find a metastable wurtzite alloy at an intermediate composition between cubic endpoint compounds, contrasting with solid solutions or cubic composites (ZnS:CuyS) from the literature. Second, structural transformations correlate with shifts in hole conductivity and absorption; specifically, conductivity increases at the wurtzite phase transformation (x ≈ 0.19). Third, conductivity and optical transparency are optimized within a "TC regime" of 0.10

Multivariate Analysis on Dynamic Car-Following Data of Non-lane-Based Traffic Environments

The difficulties of the microscopic models in accurate representation of the real traffic phenomena stem from its complexities in the collection and processing of reliable time-series car-following data of non-lane-based traffic environments. Proper estimation of car-following data can suitably ameliorate the realism of traffic sub-models and is still a demanding task. This study describes an image-based in-vehicle trajectory data collection system for the estimation of reliable dynamic time-series data, using camera calibration and in-vehicle GPS information. A copula-based methodological framework is also investigated in this study for evaluating safety in the car-following processes, by accommodating the dependence structure of longitudinal gap, centerline separation and vehicle speeds. Results of the study demonstrated the importance of centerline separation in apprehending the car-following processes. In particular, the probability of maintaining lower gaps increases with the decrease in speed and increase in centerline separation. A 15–20% reduction in the longitudinal gaps is observed for speeds greater than 60 kmph. As importantly, the study recommends the applicability of tri-variate Gaussian copula in assessing the safety or ‘safe distance-keeping’ criteria of drivers in the car-following processes, which can indeed augment the accurate representation of drivers’ behavior and development of the car-following models, advanced driver assistance systems and for safety evaluation in the car-following process of non-lane-based traffic environments.

Motion Estimation for Fisheye Video With an Application to Temporal Resolution Enhancement

Surveying wide areas with only one camera is a typical scenario in surveillance and automotive applications. Ultra wide-angle fisheye cameras employed to that end produce video data with characteristics that differ significantly from conventional rectilinear imagery as obtained by perspective pinhole cameras. Those characteristics are not considered in typical image and video processing algorithms such as motion estimation, where translation is assumed to be the predominant kind of motion. This contribution introduces an adapted technique for use in block-based motion estimation that takes into the account the projection function of fisheye cameras and thus compensates for the non-perspective properties of fisheye videos. By including suitable projections, the translational motion model that would otherwise only hold for perspective material is exploited, leading to improved motion estimation results without altering the source material. In addition, we discuss extensions that allow for a better prediction of the peripheral image areas, where motion estimation falters due to spatial constraints, and further include calibration information to account for lens properties deviating from the theoretical function. Simulations and experiments are conducted on synthetic as well as real-world fisheye video sequences that are part of a data set created in the context of this paper. Average synthetic and real-world gains of 1.45 and 1.51 dB in luminance PSNR are achieved compared against conventional block matching. Furthermore, the proposed fisheye motion estimation method is successfully applied to motion compensated temporal resolution enhancement, where average gains amount to 0.79 and 0.76 dB.

Predição de classes de solos com dados coletados em pixels delimitados por buffers em perfis de solo georreferenciados

Digital soil mapping studies (MDS) have used legacy maps as the main source of information for calibration of predictor models. However new approaches are needed with techniques that allow the use of information contained in georeferenced soil profiles, allowing the application of MDS in sampled areas that do not provide conventional soil maps. The objective of this study was to evaluate the performance in the prediction of soil occurrence of samples collected in pixels of profiles of georeferenced soils and in pixels collected in buffers with radius of 50, 100, 150, 200 and 250 m of soil profiles in the Lajeado Grande and Santo Cristo Rivers Watersheds. Two areas with availability of soil survey data published at scale 1: 50,000 were used for the study. For prediction of the occurrence of soil classes, ten predictive variables were generated from a digital elevation model with spatial resolution of 30 m. For the prediction, Random Forest algorithm was used. The predicted maps were evaluated for accuracy in relation to soil profiles and the reproducibility of conventional maps. The use of the sampling pixels collected in the buffers did not significantly alter the overall accuracy of the predicted maps in the Lajeado Grande river watershed, but allowed a 15.6% the gain at overall accuracy the Santo Cristo river watershed. The use of georeferenced profiles resulted in predicted maps with overall accuracy greater than 75% and agreement of reproducibility equal to or high than 67% in relation to the conventional map.

The Influence of Calibration Curve Construction and Composition on the Accuracy and Precision of Radiocarbon Wiggle-Matching of Tree Rings, Illustrated by Southern Hemisphere Atmospheric Data Sets from AD 1500–1950

ABSTRACTThis research investigates two factors influencing the ability of tree-ring data to provide accurate 14C calibration information: the fitness and rigor of the statistical model used to combine the data into a curve; and the accuracy, precision and reproducibility of the component 14C data sets. It presents a new Bayesian spline method for calibration curve construction and tests it on extant and new Southern Hemisphere (SH) data sets (also examining their dendrochronology and pretreatment) for the post-Little Ice Age (LIA) interval AD 1500–1950. The new method of construction allows calculation of component data offsets, permitting identification of laboratory and geographic biases. Application of the new method to the 10 suitable SH 14C data sets suggests that individual offset ranges for component data sets appear to be in the region of ± 10 yr. Data sets with individual offsets larger than this need to be carefully assessed before selection for calibration purposes. We identify a potential geographical offset associated with the Southern Ocean (high latitude) Campbell Island data. We test the new methodology for wiggle-matching short tree-ring sequences and use an OxCal simulation to assess the likely precision obtainable by wiggle-matching in the post-LIA interval.

Dynamic data collection of staggered-following behavior in non-lane-based traffic streams

Different maneuvering patterns of vehicles, absence of lane discipline and interactions of a large number of vehicles with each other and with roadway features make the traffic phenomena of non-lane-based traffic streams more complex. Vehicles’ movement in weak lane discipline traffic is rather two-dimensional because they always tend to evaluate possible available gaps on the road while progressing longitudinally. Recent literature has underlined the importance of centerline separation of traffic in modeling the staggered-following behavior. However, the requirements for staggered-following trajectory data are indeed stringent. Although recent advancements in new digital technology have expedited new horizons in the field of traffic engineering, proper estimation of microscopic car-following data has still proven to be challenging. Understanding that a proper evaluation of car-following behavior in non-lane-based traffic environments requires an accurate characterization of the microscopic traffic variables and reliable experimental data, this study describes an image-based in-vehicle trajectory data collection system to process the microscopic variables (such as longitudinal gap, centerline separation, vehicle speeds and accelerations), using camera calibration and in-vehicle GPS information on straight roads. Improved accuracy in the experimental data collection, proper extraction and estimation of data can substantially enrich the understanding of riders’ behavioral phenomena from a microscopic perspective and the realism of traffic sub-models, which will result in a better prediction of microscopic simulation models.

Simple and robust calibration procedure for k-linearization and dispersion compensation in optical coherence tomography.

.In Fourier-domain optical coherence tomography (FD-OCT), proper signal sampling and dispersion compensation are essential steps to achieve optimal axial resolution. These calibration steps can be performed through numerical signal processing, but require calibration information about the system that may require lengthy and complex measurement protocols. We report a highly robust calibration procedure that can simultaneously determine correction vectors for nonlinear wavenumber sampling and dispersion compensation. The proposed method requires only two simple mirror measurements and no prior knowledge about the system’s illumination source or detection scheme. This method applies to both spectral domain and swept-source OCT systems. Furthermore, it may be implemented as a low-cost fail-safe to validate the proper function of calibration hardware such as k-clocks. We demonstrate the method’s simple implementation, effectiveness, and robustness on both types of OCT systems.

A SCiForest based semi-supervised learning method for the seismic interpretation of channel sand-body

Machine learning technology has been widely applied in the field of seismic interpretation. In most cases, machine learning assisted seismic interpretation is calibrated or constrained by wells. However, due to the limitation of drilling cost, sometimes there are only a few samples can be obtained from the well-points for a specific layer, which is insufficient to guarantee the generalization ability of supervised learning. In this article, we propose a novelty semi-supervised method by combining the unsupervised isolation forest with split-selection criterion (SCiForest) algorithm and the supervised feature selection process together. The key of the proposed method is to be able to make full use of both the self-contained distribution information of multiple seismic attributes and the calibration information of limited well-points at the same time. To highlight the advantages of the proposed method referred to conventional supervised and unsupervised methods, we take the channel identification practice in the western Bohai Sea as a case study for comparison. Further discussion confirms that the proposed method can improve the visibility of channel effectively by fusing the relevant information in amplitude, frequency, and morphological attributes with limited calibration, which may provide a reliable alternative way for further machine learning assisted seismic interpretation.

Assessment of soil erosion risk in a typical Mediterranean environment using a high resolution RUSLE approach (Portofino promontory, NW-Italy)

ABSTRACT Particularly the Liguria region in Northern Italy is highly affected by soil erosion processes. This study was conducted in the Portofino promontory in eastern Liguria, to predict potential annual soil loss using the Revised Universal Soil Loss Equation (RUSLE). Moreover, we evaluate the relative accuracy of the predictions at detailed scale, using high resolution spatial information for model calibration. The RUSLE factors were calculated for the study area based on terrain survey data and rain gauge measurements. The results were plotted on a 1:10,000 scale soil erosion map and subsequently compared with the European soil loss estimation method (RUSLE2015) developed by the European Joined Research Centre. This study shows that the RUSLE2015 model can be applied in a typical Mediterranean environment such as the Portofino promontory. However, the accuracy of the single factors we calculated using high resolution data sets might improve the results substantially and thus, also model efficiency.

Sub‐assembly experiments to determine PWM supply‐induced losses in electric machines

This paper presents a low-cost approach to experimentally characterise the effect of the inverter supply on the losses in an electrical machine. The set-up comprises of representative subassemblies of the stator and winding, referred to as ‘motorettes’, and a single phase, fast switching silicon-carbide-based converter. The sub-assembly-based thermal analysis has been shown to be a time and cost-effective method to examine winding loss, over a range of operating conditions. In addition to the slot to stator thermal resistance and capacitance. This provides critical information for thermal model calibration and produces more accurate thermal and loss predictions of the full machine behaviour. A test arrangement has been devised to replicate the magnetic excitation of the electrical machine stator during normal operation. This builds upon previous techniques, to allow iron loss to be investigated. Through multiple tests using DC, AC, and PWM-AC supplies, a 20% increase in iron loss is observed due to PWM effects.

Scale-Free Vision-Based Aerial Control of a Ground Formation With Hybrid Topology

We present a novel vision-based control method to make a group of ground mobile robots achieve a specified formation shape with unspecified size. Our approach uses multiple aerial control units equipped with downward-facing cameras, each observing a partial subset of the multirobot team. The units compute the control commands from the ground robots’ image projections, using neither calibration nor scene scale information, and transmit them to the robots. The control strategy relies on the calculation of image similarity transformations, and we show it to be asymptotically stable if the overlaps between the subsets of controlled robots satisfy certain conditions. The presence of the supervisory units, which coordinate their motions to guarantee a correct control performance, gives rise to a hybrid system topology. All in all, the proposed system provides relevant practical advantages in simplicity and flexibility. Within the problem of controlling a team shape, our contribution lies in addressing several simultaneous challenges: the controller needs only partial information of the robotic group, does not use distance measurements or global reference frames, is designed for unicycle agents, and can accommodate topology changes. We present illustrative simulation results.

Averaging Pixel Current Adjustment Technique for Reducing Fixed Pattern Noise in the Bolometer-Type Uncooled Infrared Image Sensor.

In this paper, we propose an averaging pixel current adjustment technique for reducing fixed pattern noise (FPN) in the bolometer-type uncooled infrared image sensor. The averaging pixel current adjustment technique is composed of active pixel, reference pixel, and calibration circuit. Polysilicon resistors were used in each active pixel and reference pixel. Resistance deviation among active pixels integrated with the same resistance value cause FPN. The principle of the averaging pixel current adjustment technique for removing FPN is based on the subtraction of dark current of the active pixel from the dark current of the reference pixel. The subtracted current is converted into the voltage, which contains pixel calibration information. The calibration circuit is used to adjust the calibration current. After calibration, the nano-ampere current is output with small deviation. The proposed averaging pixel current adjustment technique is implemented by a chip composed of a pixel array, a calibration circuit, average current generators, and readout circuits. The chip was fabricated using a standard 0.35 μm CMOS process and its performance was evaluated.

Interpreting CSEM data in complex resistivity regime

CSEM has been applied as a risk mitigation tool in the Krishna-Godavari Basin, East Coast India. A workflow for application of CSEM in a portfolio ranking process is described, ranging from feasibility assessment to interpretation and post-drilling analysis. Data interpretation was based on relative response analysis, unconstrained inversion and 3D modelling. A major challenge, encountered in the data interpretation was the lack of suitable calibration areas for the interpretation model. Nevertheless, several robust resistivity anomalies were identified, which were then prioritised for drilling. The drilling of a CSEM positive prospect yielded commercial hydrocarbons. This additional calibration information, obtained from the well, was then fed back into the integration work-flow and robustness analysis for the previously lower-ranked resistors. Even using this more complex model, the presence of the resistors was confirmed. This motivated Reliance to review the seismic to upgrade the CSEM leads to prospects.

Comparison of TCD and SED methods in fatigue lifetime assessment

This paper assesses the accuracy and reliability of the Theory of Critical Distances (TCD) and the Strain Energy Density (SED) approach in estimating the lifetime of plain and notched specimens subjected to cyclic loading. To validate the two approaches for plain and notched components under uniaxial and multiaxial fatigue loading, a large bulk of experimental data taken from the literature was re-analyzed, with the state variables, i.e. the stress distributions and the strain energy density, being calculated via the Finite Element (FE) method. The results obtained demonstrate that both the TCD and the SED approach can provide highly accurate fatigue life estimation. In addition, these two approaches require little computational effort and little calibration information to be implemented and used for fatigue design in situations of practical interest.

Absolute dosimetry with polymer gels—a TLD reference system

Background and purpose. Absolute dosimetry in 3D with polymer gels (PG) is generally complicated and usually requires a second independent measurement with conventional detectors. This is why, PG are often used only for relative dosimetry. To overcome this drawback, we combine PG with a 1D thermoluminescence (TL) detector within the same measurement. The TL detector information is then used as additional information for calibration of the gel. Materials and methods. The PAGAT dosimetry gel was used in combination with TLD600 (LiF:Mg,Ti). TL detectors were attached on the surface of the PG container placed inside a cylindrical phantom. To test the usability of this setup, two irradiation geometries were carried out: (a) homogeneous target coverage and (b) small-field irradiation. PG was evaluated with magnetic resonance imaging (MRI) and the TL detectors with a Harshaw 5500 hot gas reader. Results. PG dosimetry alone showed deviations of up to 4% as compared to calculations. Including additionally the dose information of the TL detectors for PG calibration, this deviation was decreased to less than 1% for both irradiation geometries. This is also reflected by the very high -passing rates of > 96% (3%/3 mm) and >93% (2%/2 mm), respectively. Conclusion. This study presents a novel method combining 3D PG and TL dose measurements for the purpose of absolute 3D dose measurements that can also be applied in complex anthropomorphic phantoms using only a single measurement. The method was validated for two different irradiation geometries including a homogeneous large field as well as a small field irradiation with sharp dose gradients.

Decentralized and resource-efficient self-calibration of visual sensor networks

Many multi-camera applications rely on the knowledge of the spatial relationship among the individual nodes. However, establishing such a network-wide calibration is typically a time-consuming task and requires user interaction. In this paper we present a decentralized and resource-aware algorithm for estimating the poses of all network nodes without any user interaction. This self-calibration of the network is achieved in two steps: First, overlapping camera pairs estimate relative positions and orientations by exchanging locally measured distances and angles to detected objects. Second, calibration information of overlapping cameras is spread throughout the network such that poses of non-overlapping cameras can also be estimated. Our approach does not rely on a priori topological information and delivers the extrinsic camera parameters with respect to a common coordinate system. In a simulation study we analyze the performance of our approach concerning the achieved spatial accuracy and computational effort considering noisy measurements and different communication schemes.

A flexible multi-view calibration and 3D measurement method based on digital fringe projection

Multi-view systems are an effective scheme for solving the problem of a small field-of-view and self-occlusion in optical 3D measurements. However, due to the dispersed distribution of views and the lack of a common field-of-view, the problem of global calibration is difficult and essential. A new method is proposed, by which digital fringe projection and a phase map are used to establish global calibration information. Firstly, fringes are projected to the field of the system. By using a phase unwrapping algorithm, an absolute phase map is obtained. The projector is deemed as the reverse of a camera, which can be calibrated in a similar way to that of the camera. Therefore, the parameters of the cameras, projector and the location of each calibration plane are calculated, and the transformation relationship of adjacent cameras is obtained. Secondly, the phase is used in 3D measurement as well as the global registration of views. Sub-pixel point matching and 3D reconstruction is performed according to the phase map. Global system parameters are optimized by minimizing the reconstruction errors, and precise calibration results can be achieved. With this method, a large-sized calibration target and other auxiliary calibration devices are not required. It is reliable and easy to implement multi-view calibration and reconstruction. The calibration model and calculation processing are simple. The experiment is carried out on a multi-view 3D measurement system. It is shown that high precision multi-view calibration and reconstruction results are obtained.