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Journal articles
Improving spatio-temporal resolution of infrared images to detect thermal activity of defect at the surface of inorganic glass
Abstract : This paper proposes a noise suppression methodology to improve the spatio-temporal resolution of infra-red images. The methodology is divided in two steps. The first one consists in removing the noise from the temporal signal at each pixel. Three basic temporal filters are considered for this purpose: average filter, cost function minimization (FIT) and short time Fast Fourier Transform approach (STFFT). But while this step effectively reduces the temporal signal noise at each pixel, the infrared images may still appear noisy. This is due to a random distribution of a residual offset value of pixels signal. Hence 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 synthetic images built from infrared computer-generated images combined with experimental noise. 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. The three basic temporal filters are quantitatively compared and contrasted. Results obtained demonstrate that, contrarily to a basic spatio-temporal approach, the denoising method proposed is suitable to characterize low thermal activity combined to strong spatial gradients induced by cyclic heterogeneous deformations.
Keywords :
Experimental mechanics
Cyclic mechanical loading
De-noising
Cost functions
Fast Fourier transforms
Infrared imaging
Indentation
Glass
Pixels
Spatio-temporal resolution
Spatio-temporal approach
Heterogeneous deformation
Soda Lime glass
Computer-generated images
Thermography (imaging)
Temperature distribution
Temperature
Surface defects
Cited literature [28 references]
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01372804
Contributor : Laurent Jonchère <>
Submitted on : Thursday, May 7, 2020 - 2:57:05 PM
Last modification on : Wednesday, September 23, 2020 - 4:17:17 PM
Contributor : Laurent Jonchère <>
Submitted on : Thursday, May 7, 2020 - 2:57:05 PM
Last modification on : Wednesday, September 23, 2020 - 4:17:17 PM
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b_Corvec2016.pdf
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