Spatial-Spectral Representation for X-Ray Fluorescence Image Super-Resolution

Dai, Qiqin; Pouyet, Emeline; Cossairt, Oliver; Walton, Marc; Katsaggelos, Aggelos K.

doi:10.1109/TCI.2017.2703987

Spatial-Spectral Representation for X-Ray Fluorescence Image Super-Resolution

Journal Article · Fri Sep 01 04:00:00 EDT 2017 · IEEE Transactions on Computational Imaging (CD-ROM)

DOI:https://doi.org/10.1109/TCI.2017.2703987· OSTI ID:1487462

Dai, Qiqin ^[1]; Pouyet, Emeline; Cossairt, Oliver; Walton, Marc;

Northwestern University

X-ray fluorescence (XRF) scanning of works of art is becoming an increasing popular nondestructive analyticalmethod. The high quality XRF spectra is necessary to obtain significant information on both major and minor elements used for characterization and provenance analysis. However, there is a tradeoff between the spatial resolution of an XRF scan and the signalto- noise ratio (SNR) of each pixel’s spectrum, due to the limited scanning time. In this project, we propose an XRF image super-resolution method to address this tradeoff; thus, obtaining a high spatial resolution XRF scan with high SNR. We fuse a lowresolution XRF image and a conventional RGB high-resolution image into a product of both high spatial and high spectral resolution XRF image. There is no guarantee of a one to one mapping between XRF spectrum and RGB color since, for instance, paintings with hidden layers cannot be detected in visible but can in X-ray wavelengths. We separate the XRF image into the visible and nonvisible components. The spatial resolution of the visible component is increased utilizing the high-resolution RGB image, whereas the spatial resolution of the non-visible component is increased using a total variation super-resolution method. Finally, the visible and nonvisible components are combined to obtain the final result.

Research Organization:: Northwestern Univ., Evanston, IL (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22)

DOE Contract Number:: NA0002520

OSTI ID:: 1487462

Journal Information:: IEEE Transactions on Computational Imaging (CD-ROM), Journal Name: IEEE Transactions on Computational Imaging (CD-ROM) Journal Issue: 3 Vol. 3; ISSN 2334-0118

Publisher:: IEEE

Country of Publication:: United States

Language:: English

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