Chapter4 A New Denoising Methodology to Keep the Spatial Resolution of IR Images Equal to 1 Pixel Guillaume Corvec, Eric Robin, Jean-Benoît Le Cam, Jean-Christophe Sangleboeuf, and Pierre Lucas Abstract This paper proposes a noise suppression methodology to improve the spatio-temporal resolution of infrared images. The methodology is divided in two steps. The first one consists in removing the noise from the temporal signal at each pixel. In the second step, the residual offset is identified by considering thermal images for which no mechanical loading is applied. In this case, the temperature variation field is homogeneous and the value of temperature variation at each pixel is theoretically equal to zero. The method is first tested on numerical images. The results demonstrate that this approach permits to keep the spatial resolution of infrared images equal to 1 pixel. The methodology is then applied to characterize thermal activity of a defect at the surface of inorganic glass submitted to cyclic mechanical loading. Keywords Infrared thermography • Denoising • Experimental mechanics • Soda lime glass • Indentation 4.1 Introduction Thermal and calorimetric effects accompanying the deformation of materials are widely studied in literature to investigate thermomechanical couplings, fatigue and failure, non-exhaustively. Infrared thermography has proved to be a relevant technique for studying engineering materials such as steel, aluminum and composites. Experiments in this field consist in applying a mechanical loading and in measuring the temperature field induced at the material surface using an infrared camera. Temperature variation field is generally processed from temperature field to determine hydrostatic stress field by using thermoelastic stress analysis (TSA) [1], to investigate calorimetric response of materials or to access mechanical dissipation [2]. The results obtained provide information of importance for the understanding of deformation and damage mechanisms such as Luder’s bands [3], fatigue [4, 5] strain localization [6] or strain-induced crystallization [7, 8]. In such conditions noise pollution does not alter significantly the measured temperature variation field and can be removed with the help of non-uniformity [9] correction of the infrared detector combined with a spatio-temporal filtering process. If the signal-to-noise ratio of infrared images in terms of temperature variation becomes low, processing infrared images is more complicated. Recent work has been carried out on this topic to characterize temperature variation gradients induced during a cyclic three points bending test applied to soda lime glass [10] and during cyclic compression test applied to a chalcogenide glass disk with a hole [11]. It is all the more complicated if higher gradients are induced during the mechanical loading. For example in the imprint zone after identation process [12], the use of an average filter in these conditions can smooth or remove the thermal activity. The present study aims at proposing a methodology to significantly improve the spatio-temporal resolution of thermal images in challenging conditions. G. Corvec • E. Robin ( ) • J.-B. Le Cam • J.-C. Sangleboeuf Université de Rennes 1, Institut de Physique UMR 6251, CNRS/Université de Rennes 1, Campus de Beaulieu, Bât. 10B, 35042, Rennes Cedex, France e-mail: eric.robin@univ-rennes1.fr P. Lucas Arizona Materials Laboratory, 4715 East Fort Lowell Rd, Tucson, AZ 85712, USA © The Society for Experimental Mechanics, Inc. 2018 A. Baldi et al. (eds.), Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 8, Conference Proceedings of the Society for Experimental Mechanics Series, DOI 10.1007/978-3-319-62899-8_4 21
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