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Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques

Abstract : The goal of this paper is to explore the potential interest of image fusion in the context of multimodal scanning electron microscope (SEM) imaging. In particular, we aim at merging the backscattered electron images that usually have a high spatial resolution but do not provide enough discriminative information to physically classify the nature of the sample, with energy-dispersive X-ray spectroscopy (EDX) images that have dis-criminative information but a lower spatial resolution. The produced images are named enhanced EDX. To achieve this goal, we have compared the results obtained with classical pansharpening techniques for image fusion with an original approach tailored for multimodal SEM fusion of information. Quantitative assessment is obtained by means of two SEM images and a simulated dataset produced by a software based on PENELOPE.
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https://hal.archives-ouvertes.fr/hal-01688728
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Submitted on : Friday, January 19, 2018 - 4:16:56 PM
Last modification on : Wednesday, November 17, 2021 - 12:27:15 PM
Long-term archiving on: : Thursday, May 24, 2018 - 7:37:43 AM

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Gianni Franchi, Jesus Angulo, Maxime Moreaud, Loïc Sorbier. Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques. Journal of Microscopy, Wiley, 2018, 269 (1), pp.94 - 112. ⟨10.1111/jmi.12612⟩. ⟨hal-01688728⟩

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