Three-dimensional scanning of specular and diffuse metallic surfaces using an infrared technique

For the past two decades, the need for three-dimensional (3-D) scanning of industrial objects has increased significantly and many experimental techniques and commercial solutions have been proposed. However, difficulties remain for the acquisition of optically non-cooperative surfaces, such as transparent or specular surfaces. To address highly reflective metallic surfaces, we propose the extension of a technique that was originally dedicated to glass objects. In contrast to conventional active triangulation techniques that measure the reflection of visible radiation, we measure the thermal emission of a surface, which is locally heated by a laser source. Considering the thermophysical properties of metals, we present a simulation model of heat exchanges that are induced by the process, helping to demonstrate its feasibility on specular metallic surfaces and predicting the settings of the system. With our experimental device, we have validated the theoretical modeling and computed some 3-D point clouds from specular surfaces of various geometries. Furthermore, a comparison of our results with those of a conventional system on specular and diffuse parts will highlight that the accuracy of the measurement no longer depends on the roughness of the surface

Linear chemically sensitive electron tomography using DualEELS and dictionary-based compressed sensing

We have investigated the use of DualEELS in elementally sensitive tilt series tomography in the scanning transmission electron microscope. A procedure is implemented using deconvolution to remove the effects of multiple scattering, followed by normalisation by the zero loss peak intensity. This is performed to produce a signal that is linearly dependent on the projected density of the element in each pixel. This method is compared with one that does not include deconvolution (although normalisation by the zero loss peak intensity is still performed). Additionaly, we compare the 3D reconstruction using a new compressed sensing algorithm, DLET, with the well-established SIRT algorithm. VC precipitates, which are extracted from a steel on a carbon replica, are used in this study. It is found that the use of this linear signal results in a very even density throughout the precipitates. However, when deconvolution is omitted, a slight density reduction is observed in the cores of the precipitates (a so-called cupping artefact). Additionally, it is clearly demonstrated that the 3D morphology is much better reproduced using the DLET algorithm, with very little elongation in the missing wedge direction. It is therefore concluded that reliable elementally sensitive tilt tomography using EELS requires the appropriate use of DualEELS together with a suitable reconstruction algorithm, such as the compressed sensing based reconstruction algorithm used here, to make the best use of the limited data volume and signal to noise inherent in core-loss EELS

Modeling Envisat RA-2 waveforms in the coastal zone: case-study of calm water contamination

Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This paper examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10 km2 island in the NW Mediterranean). Forty-six repeat passes were analysed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modelling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges, but also greatly enhance the study of storm surges and other coastal phenomena

Robust regularized singular value decomposition with application to mortality data

We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year. The RobRSVD is formulated as a penalized loss minimization problem where a robust loss function is used to measure the reconstruction error of a low-rank matrix approximation of the data, and an appropriately defined two-way roughness penalty function is used to ensure smoothness along each of the two functional domains. By viewing the minimization problem as two conditional regularized robust regressions, we develop a fast iterative reweighted least squares algorithm to implement the method. Our implementation naturally incorporates missing values. Furthermore, our formulation allows rigorous derivation of leave-one-row/column-out cross-validation and generalized cross-validation criteria, which enable computationally efficient data-driven penalty parameter selection. The advantages of the new robust method over nonrobust ones are shown via extensive simulation studies and the mortality rate application.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS649 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org