Sensor Noise Modeling by Stacking Pseudo-Periodic Grid Images Affected by Vibrations

International audienceThis letter addresses the problem of noise estimation in raw images from digital sensors. Assuming that a series of images of a static scene are available, a possibility is to characterize the noise at a given pixel by considering the random fluctuations of the gray level across the images. However, mechanical vibrations, even tiny ones, affect the experimental setup, making this approach ineffective. The contribution of this letter is twofold. It is shown that noise estimation in the presence of vibrations is actually biased. Focusing on images of a pseudo-periodic grid, an algorithm to discard their effect is also given. An application to the generalized Anscombe transform is discussed

On noise reduction in strain maps obtained with the grid method by averaging images affected by vibrations

International audienceAny image-based contactless measurement system has a limited resolution because of sensor noise. If the sensor is rigorously static with respect to the imaged object, a possibility is to reduce noise by averaging images acquired at different times. This paper discusses images of a pseudo-periodic grid used in experimental solid mechanics to give estimations of in-plane displacement and strain components of a deformed flat specimen. Because of the magnification factor which is employed, the grid images are often affected by residual vibrations, thereby invalidating the assumption that the sensor is static. The averaged grid image is thus a biased estimator of the unknown noise-free image. In spite of this, we prove that the retrieved displacement and strain components still benefit from noise reduction by time-averaging. A theoretical model is discussed, and experiments on real and synthetic data sets are provided

On noise prediction in maps obtained with global DIC

International audienceA predictive formula giving the measurement resolution in displacement maps obtained using Digital Image Correlation was proposed some years ago in the literature. The objective of this paper is to revisit this formula and to propose a more general one which takes into account the influence of subpixel interpolation for the displacement. Moreover, a noiseless DIC tangent operator is defined to also minimize noise propagation from images to displacement maps. Simulated data enable us to assess the improvement brought about by this approach. The experimental validation is then carried out by assessing the noise in displacement maps deduced from a stack of images corrupted by noise. It is shown that specific image pre-processing tools are required to correctly predict the displacement resolution. This image pre-processing step is necessary to correctly account for the fact that noise in images is signal-dependent, and to get rid of parasitic micro-movements between camera and specimen that were experimentally observed and which corrupt noise estimation. Obtained results are analyzed and discussed

Stabilizing Heteroscedastic Noise With the Generalized Anscombe Transform. Application to Accurate Prediction of the Resolution in Displacement and Strain Maps Obtained With the Grid Method.

International audienceThe objective of this paper is to show that it is possible to predict the noise level in displacement and strain maps obtained with the grid method, but that actual noise of camera sensors being heteroscedastic, it is necessary to stabilize this noise in grid images prior to employing the predicting formulas. The procedure used for this purpose relies on the Generalized Anscombe Transform. This transform is first described. It is then shown that experimental and theoretical resolutions in strain maps obtained with the grid method are in good agreement when this transform is employed

On the propagation of camera sensor noise to displacement maps obtained by DIC - an experimental study

International audienceThis paper focuses on one of the metrological properties of DIC, namely displacement resolution. More specifically, the study aims to validate, in the environment of an experimental mechanics laboratory, a recent generalized theoretical prediction of displacement resolution. Indeed, usual predictive formulas available in the literature neither take into account sub-pixel displacement, nor have been validated in an experimental mechanics laboratory environment, nor are applicable to all types of DIC (Global as well as Local). Here, the formula used to account for sub-pixel displacements is first recalled, and an accurate model of the sensor noise is introduced. The hypotheses required for the elaboration of this prediction are clearly stated. The formula is then validated using experimental data. Since rigid body motion between the specimen and the camera impairs the experimental data, and since sensor noise is signal-dependent, particular tools need to be introduced in order to ensure the consistency between the observed image noise and the model on which prediction hypotheses are based. Pre-processing tools introduced for another full-field measurement approach, namely the Grid Method, are employed to address these issues

Effect of Sensor Noise on the Resolution and Spatial Resolution of Displacement and Strain Maps Estimated with the Grid Method

International audienceThis paper deals with noise propagation from camera sensor to displacement and strain maps when the grid method is employed to estimate these quantities. It is shown that closed-form equations can be employed to predict the link between metrological characteristics such as resolution and spatial resolution in displacement and strain maps on the one hand and various quantities characterising grid images such as brightness, contrast and standard deviation of noise on the other hand. Various numerical simulations confirm first the relevance of this approach in the case of an idealised camera sensor impaired by a homoscedastic Gaussian white noise. Actual CCD or CMOS sensors exhibit, however, a heteroscedastic noise. A pre-processing step is therefore proposed to first stabilise noise variance prior to employing the predictive equations, which provide the resolution in strain and displacement maps due to sensor noise. This step is based on both a modelling of sensor noise and the use of the generalised Anscombe transform to stabilise noise variance. Applying this procedure in the case of a translation test confirms that it is possible to model correctly noise propagation from sensor to displacement and strain maps, and thus also to predict the actual link between resolution, spatial resolution and standard deviation of noise in grid images

Characterization Of Wave Propagation Through Composite Laminates

Structural Health Monitoring (SHM) seeks to develop systems for data collection, verification, and analysis to detect the potential for critical damage to occur in engineering structures. Composite panels are engineering structures that are susceptible to damages such as delamination and fiber breakage which greatly reduce the safety and performance of the structure. For composite materials that are widely used in aviation, early detection of such damage is important to prevent failure while the component is in flight. A common SHM method for damage assessment of composites is the Lamb wave propagation technique, whereby waves may be introduced into the composite panel via piezoelectric transducers. The propagating waves are measured after traveling through the region of interest to detect damage present in that region. Scanning laser vibrometry is a method often used to detect wave propagation patterns. The method is beneficial in that it is noncontact, nondestructive, and can be applied to virtually all geometries. Wave propagation patterns in composite panels are different from those seen in isotropic plates due to their anisotropy and the viscoelastic nature of the matrix materials. The use of a scanning laser vibrometer (SLV) to characterize wave propagation through a composite panel was explored in the present research. The characteristics of interest were the directionality of the propagating wave\u27s amplitude, velocity, and attenuation. Thin lead-zirconate-titanate (PZT) actuators were bonded to an undamaged carbon/epoxy composite panel and pulsed to extract the wavefields using the SLV. Numerical simulations of the experiments were also performed to verify the results

Novel Approaches for Nondestructive Testing and Evaluation

Nondestructive testing and evaluation (NDT&E) is one of the most important techniques for determining the quality and safety of materials, components, devices, and structures. NDT&E technologies include ultrasonic testing (UT), magnetic particle testing (MT), magnetic flux leakage testing (MFLT), eddy current testing (ECT), radiation testing (RT), penetrant testing (PT), and visual testing (VT), and these are widely used throughout the modern industry. However, some NDT processes, such as those for cleaning specimens and removing paint, cause environmental pollution and must only be considered in limited environments (time, space, and sensor selection). Thus, NDT&E is classified as a typical 3D (dirty, dangerous, and difficult) job. In addition, NDT operators judge the presence of damage based on experience and subjective judgment, so in some cases, a flaw may not be detected during the test. Therefore, to obtain clearer test results, a means for the operator to determine flaws more easily should be provided. In addition, the test results should be organized systemically in order to identify the cause of the abnormality in the test specimen and to identify the progress of the damage quantitatively

Optimal digital color image correlation

International audienceWithin the context of Digital Image Correlation (DIC), the optimal treatment of color images is considered. The mathematical bases of a weighted 3-field image correlation are first introduced , which are relevant for RGB encoded images. In this framework, noise characterization methods are developed as noise properties dictate the best suited metric to compare images. Consistent ways to process an image from elementary Bayer matrices are derived. Last, a case study on uncertainty quantification is performed

Photometry, Centroid and Point-Spread Function Measurements in the LSST Camera Focal Plane Using Artificial Stars

The Vera C. Rubin Observatory's LSST Camera pixel response has been characterized using laboratory measurements with a grid of artificial stars. We quantify the contributions to photometry, centroid, point-spread function size, and shape measurement errors due to small anomalies in the LSSTCam CCDs. The main sources of those anomalies are quantum efficiency variations and pixel area variations induced by the amplifier segmentation boundaries and "tree-rings" -- circular variations in silicon doping concentration. We studied the effects using artificial stars projected on the sensors and find that the resulting measurement uncertainties pass the ten-year LSST survey science requirements. In addition, we verify that the tree-ring effects can be corrected using flat-field images if needed, because the astronomic shifts and shape measurement errors they induce correlate well with the flat-field signal. Nevertheless, further sensor anomaly studies with on-sky data should probe possible temporal and wavelength-dependent effects.Comment: Submitted to PAS