Publications et conférences

Journaux internationaux

  1. Monier, E., Oberlin, T., Brun, N., Li, X., Tencé, M., & Dobigeon, N. (2020). Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling. Ultramicroscopy. https://doi.org/10.1016/j.ultramic.2020.112993

    This paper discusses the reconstruction of partially sampled spectrum-images to accelerate the acquisition in scanning transmission electron microscopy (STEM). The problem of image reconstruction has been widely considered in the literature for many imaging modalities, but only a few attempts handled 3D data such as spectral images acquired by STEM electron energy loss spectroscopy (EELS). Besides, among the methods proposed in the microscopy literature, some are fast but inaccurate while others provide accurate reconstruction but at the price of a high computation burden. Thus none of the proposed reconstruction methods fulfills our expectations in terms of accuracy and computation complexity. In this paper, we propose a fast and accurate reconstruction method suited for atomic-scale EELS. This method is compared to popular solutions such as beta process factor analysis (BPFA) which is used for the first time on STEM-EELS images. Experiments based on real as synthetic data will be conducted.

     @article{Monier_Ultramicroscopy_2020,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Li, X. and Tenc\'e, M. and Dobigeon, N.},
      title = {Fast reconstruction of atomic-scale {STEM-EELS} images from sparse sampling},
      journal = {Ultramicroscopy},
      year = {2020},
      url = {https://doi.org/10.1016/j.ultramic.2020.112993},
      arxiv = {https://arxiv.org/abs/2002.01225/}
    }
     
  2. Monier, E., Oberlin, T., Brun, N., Tencé, M., de Frutos, M., & Dobigeon, N. (2018). Reconstruction of partially sampled multi-band images – Application to EELS microscopy. IEEE Trans. Computational Imaging, 4(4), 585–598. https://ieeexplore.ieee.org/document/8447232

    Electron microscopy has shown to be a very powerful tool to map the chemical nature of samples at various scales down to atomic resolution. However, many samples can not be analyzed with an acceptable signal-to-noise ratio because of the radiation damage induced by the electron beam. This is particularly crucial for electron energy loss spectroscopy (EELS), which acquires spectral-spatial data and requires high beam intensity. Since scanning transmission electron microscopes (STEM) are able to acquire data cubes by scanning the electron probe over the sample and recording a spectrum for each spatial position, it is possible to design the scan pattern and to sample only specific pixels. As a consequence, partial acquisition schemes are now conceivable, provided a reconstruction of the full data cube is conducted as a postprocessing step. This paper proposes two reconstruction algorithms for multiband images acquired by STEM-EELS which exploits the spectral structure and the spatial smoothness of the image. The performance of the proposed schemes is illustrated thanks to experiments conducted on a realistic phantom dataset as well as real EELS spectrum-images.

     @article{monier2018tci,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Tenc\'e, M. and de Frutos, M. and Dobigeon, N.},
      title = {Reconstruction of partially sampled multi-band images -- {A}pplication to {EELS} microscopy},
      journal = {IEEE Trans. Computational Imaging},
      year = {2018},
      month = dec,
      volume = {4},
      number = {4},
      pages = {585--598},
      url = {https://ieeexplore.ieee.org/document/8447232},
      arxiv = {https://arxiv.org/abs/1802.10066}
    }
     

Conférences internationales

  1. Monier, E., Oberlin, T., Brun, N., & Dobigeon, N. (2019, July). Reconstruction of partially sampled STEM-EELS images with atomic resolution. Proc. Workshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS).
     @inproceedings{monier2019spars,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Dobigeon, N.},
      title = {Reconstruction of partially sampled {STEM-EELS} images with atomic resolution},
      booktitle = {Proc. Workshop on Signal Processing with Adaptative Sparse Structured Representations (SPARS)},
      address = {Toulouse, France},
      month = jul,
      year = {2019},
      pages = {}
    }
     
  2. Monier, E., Oberlin, T., Brun, N., de Frutos, M., Tencé, M., & Dobigeon, N. (2018, September). Reconstruction of partially sampled EELS images. Proc. IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS). https://ieeexplore.ieee.org/document/8747104

    Electron microscopy has shown to be a very powerful tool to deeply analyze the chemical composition at various scales. However, many samples can not be analyzed with an acceptable signal-to-noise ratio because of the radiation damage induced by the electron beam. Particularly, electron energy loss spectroscopy (EELS) which acquires a spectrum for each spatial position requires high beam intensity. Scanning transmission electron microscopes (STEM) sequentially acquire data cubes by scanning the electron probe over the sample and record a spectrum for each spatial position. Recent works developed new acquisition procedures, which allow for partial acquisition schemes following a predetermined scan pattern. A reconstruction of the full data cube is conducted as a post-processing step. A multi-band image reconstruction procedure which exploits the spectral structure and the spatial smoothness of STEM-EELS images is explained here. The performance of the proposed scheme is illustrated thanks to experiments conducted on a realistic phantom dataset as well as real EELS spectrum-image.

     @inproceedings{monier2018whispers,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and de Frutos, M. and Tenc\'e, M. and Dobigeon, N.},
      title = {Reconstruction of partially sampled {EELS} images},
      booktitle = {Proc. IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS)},
      year = {2018},
      month = sep,
      address = {Amsterdam, Netherlands},
      pages = {},
      url = {https://ieeexplore.ieee.org/document/8747104}
    }
     
  3. Monier, E., Oberlin, T., Brun, N., & Dobigeon, N. (2018, June). A Partial Random Sampling STEM Procedure For Sensitive Samples. Proc. JEELS Conference.
     @inproceedings{monier2018jeels,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Dobigeon, N.},
      title = {A Partial Random Sampling {STEM} Procedure For Sensitive Samples},
      booktitle = {Proc. JEELS conference},
      address = {Porquerolles, France},
      month = jun,
      year = {2018},
      pages = {}
    }
     
  4. Monier, E., Oberlin, T., Brun, N., Tencé, M., & Dobigeon, N. (2017). Reconstruction of randomly and partially sampled STEM spectrum-images. Microscopy & MicroAnalysis (MM), 23(S1), 170–171. https://www.cambridge.org/core/journals/microscopy-and-microanalysis/article/reconstruction-of-randomly-and-partially-sampled-stem-spectrumimages/075370ACDD54D20D2F99693B1F0CF7EC
     @inproceedings{monier2017mm,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Tenc\'e, M. and Dobigeon, N.},
      title = {Reconstruction of randomly and partially sampled {STEM} spectrum-images},
      booktitle = {Microscopy & MicroAnalysis (MM)},
      address = {Saint Louis, USA},
      volume = {23},
      issue = {S1},
      month = aug,
      year = {2017},
      pages = {170--171},
      url = {https://www.cambridge.org/core/journals/microscopy-and-microanalysis/article/reconstruction-of-randomly-and-partially-sampled-stem-spectrumimages/075370ACDD54D20D2F99693B1F0CF7EC}
    }
     
  5. Monier, E., & Chardon, G. (2017). Cramér-Rao bounds for the localization of anisotropic sources. Proc. IEEE Int. Conf. on Acoust., Speech and Signal Processing (ICASSP), 3281–3285. https://ieeexplore.ieee.org/document/7952763/

    In the most general case, source localization has to take into account the radiation pattern of the sources of interest. This is particularly important when the sensors surround the sources, and the sources are anisotropic, as is the case in several applications (EEG, speech, musical instruments, etc.). Cramer-Rao bounds for the joint estimation of the position of a source and its radiation pattern are computed for simple cases of sensor array geometries and source models, showing that a good match between the source and the model improves the Cramer-Rao bounds. It is also shown that, in general, using a model more complex than the source makes the Fisher information matrix singular. These results are supported by numerical simulations and physical interpretations.

     @inproceedings{monier2017icassp,
      title = {Cram{\'e}r-Rao bounds for the localization of anisotropic sources},
      author = {Monier, E and Chardon, G},
      booktitle = {Proc. IEEE Int. Conf. on Acoust., Speech and Signal Processing (ICASSP)},
      pages = {3281--3285},
      year = {2017},
      url = {https://ieeexplore.ieee.org/document/7952763/}
    }
     

Conferences nationales

  1. Monier, E., Oberlin, T., Brun, N., Tencé, M., de Frutos, M., & Dobigeon, N. (2019). Reconstruction de spectres-images STEM-EELS partiellement échantillonnés. Actes Du XVIième Colloque De La Société Française Des Microscopies (SFMu), 74–75.
     @inproceedings{monier2019sfmu,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Tenc\'e, M. and de Frutos, M. and Dobigeon, N.},
      title = {Reconstruction de spectres-images STEM-EELS partiellement \'echantillonn\'es},
      journal = {Actes du XVIième Colloque de la Société Française des Microscopies (SFMu)},
      year = {2019},
      month = jul,
      pages = {74--75}
    }
     
  2. Monier, E., Oberlin, T., Brun, N., & Dobigeon, N. (2017). Reconstruction de spectres-images partiellement échantillonnés en microscopie EELS. Actes Du XXVIième Colloque GRETSI.

    A recurrent problem encountered in electron microscopy is to achieve a trade-off between a correct signal-to-noise ratio and a non-destructive beam. As the scanning transmission electron microscopy can acquire spatial and spectral datacubes, one of its main advantages is the ability to acquire pixel spectra at only some spatial locations. As a consequence, partial acquisition schemes are conceivable, provided a reconstruction of the full data cube is conducted as a post-processing step. This paper proposed a reconstruction approach of EELS spectrum-images which exploits the spectral redundancy and the spatial smoothness of the image. The performance of proposed scheme is illustrated thanks to experiments conducted on a realistic dataset.

     @inproceedings{monier2017gretsi,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Dobigeon, N.},
      title = {Reconstruction de spectres-images partiellement \'echantillonn\'es en microscopie {EELS}},
      booktitle = {Actes du XXVIi\`eme Colloque GRETSI},
      year = {2017},
      address = {Juan-les-Pins, France},
      note = {in french}
    }
     

Rapports techniques

Note : Ces rapports techniques sont des versions complétées des articles de journaux listés ci-dessus.

  1. Monier, E., Oberlin, T., Brun, N., Tencé, M., Li, X., & Dobigeon, N. (2020). Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling – Complementary results. University of Toulouse, IRIT/INP-ENSEEIHT. http://dobigeon.perso.enseeiht.fr/papers/Monier_TechReport_2020.pdf
     @techreport{Monier_TechReport_2020,
      author = {Monier, E. and Oberlin, Th. and Brun, N. and Tenc\'e, M. and Li, X. and Dobigeon, N.},
      title = {Fast reconstruction of atomic-scale {STEM-EELS} images from sparse sampling -- {C}omplementary results},
      institution = {University of Toulouse, IRIT/INP-ENSEEIHT},
      address = {France},
      month = feb,
      year = {2020},
      url = {http://dobigeon.perso.enseeiht.fr/papers/Monier_TechReport_2020.pdf}
    }