Full list of Publications
Submitted papers
- "Probabilistic Spiking Neural Networks Training with Expectation-Propagation", submitted, 2023.
- "Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling", submitted, 2023. (Arxiv preprint)
- "A variational autoencoder for minimally-supervised neutron-gamma discrimination", submitted, 2023
- "Online adaptive estimation of decoherence timescales for a single qubit", submitted, 2022. (Arxiv preprint)
International journal papers
- D. Yao, P. W. R. Connolly, A. J. Sykes, Y. D. Shah, C. Accarino, J. Grant, D. R. S. Cumming, G. S. Buller, S. McLaughlin, Y. Altmann, "Rapid Single-Photon Color Imaging of Moving Objects", Optics Express, vol. 31, issue 16, 2023.
- J. Zhou, A. Abdulaziz, Y. Altmann, A. Di Fulvio, "Generalized method for the optimization of pulse shape discrimination parameters", Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol.1050, 2023.
- A. Abdulaziz, S. P. Mekhail, Y. Altmann, M. J. Padgett, S. McLaughlin, "Robust real-time imaging through flexible multimode fibers", Scientific Reports, vol. 13, 11371, 2023. (Arxiv preprint)
- S. Melidonis, P. Dobson, Y. Altmann, M. Pereyra, K. C. Zygalakis, "Efficient Bayesian computation for low-photon imaging problems", SIAM Journal on Imaging Sciences, vol. 16, Issue 3, 2023. (Arxiv preprint)
- M. Botticelli, V. Risdonne, T. Visser, C. Young, M. J. Smith, J. M. Charsley, M. Rutkauskas, Y. Altmann, D. T. Reid, "Reflecting the past, imag(in)ing the past: macro-reflection imaging of painting materials by fast MIR hyperspectral analysis". Eur. Phys. J. Plus 138, 432 (2023).
- A. Maccarone, K. Drummond, A. McCarthy, U. K. Steinlehner, J. Tachella, D. Aguirre Garcia, A. Pawlikowska, R. A. Lamb, R. K. Henderson, S. McLaughlin, Y. Altmann, G. S. Buller, "Submerged single-photon LiDAR imaging sensor used for real-time 3D scene reconstruction in scattering underwater environments", Optics Express, 31, 16690-16708, 2023
- D. Yao, S. McLaughlin, Y. Altmann, "Fast Scalable Image Restoration using Total Variation Priors and Expectation-Propagation", IEEE Trans. Image Processing, 2022. (Arxiv preprint)
- S. Shi , L. Zhang , Y. Altmann , J. Chen, "Deep Generative Model for Spatial-spectral Unmixing with Multiple Endmember Priors", IEEE Trans. Geoscience and Remote Sensing, vol. 60, 2022.
- J. Charsley, M. Rutkauskas, Y. Altmann, V. Rsidonne, M. Botticelli, M. J. Smith, C. R. T. Young, D. T. Reid, "Compressive Hyperspectral Imaging in the Molecular Fingerprint Band", Optics Express, 2022. (preprint)
- Z. Li, Y. Altmann, J. Chen, S. Mclaughlin, S. Rahardja, "Sparse Linear Spectral Unmixing of Hyperspectral images using Expectation-Propagation", IEEE Trans. Geoscience and Remote Sensing, vol. 60, 2022. (Arxiv preprint)
- D. Yao, S. McLaughlin, Y. Altmann, "Patch-Based Image Restoration using Expectation-Propagation", SIAM J. Imaging Sci., vol. 15, no. 1, 2022. (Arxiv preprint)
- S. Shi, M. Zhao, L. Zhang, Y. Altmann, J. Chen, "Probabilistic generative model for hyperspectral unmixing accounting for endmember variability", IEEE Trans. Geoscience and Remote Sensing, vol. 61, 2021.
- A. K. Eldaly, M. Fang, A. Di Fulvio, S. McLaughlin, M. Davies, Y. Altmann, Y. Wiaux, "Bayesian Activity Estimation and Uncertainty Quantification of Spent Nuclear Fuel using Passive Gamma Emission Tomography", J. Imaging, 7(10), 2021.
- N.Gaughan, J.Zhou, F.D. Becchetti, R.O. Torres-Isea, M.Febbraro, N.Zaitseva, Y.Altmann, A.Di Fulvio, "Characterization of stilbene-d12 for neutron spectroscopy without time of flight", Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol 1018, 2021.
- P. W. R. Connolly, J. Valli, Y. D. Shah, Y. Altmann, J. Grant, C. Accarino, C. Rickman, D. R. S. Cumming, G. S. Buller, "Simultaneous multi-spectral, single-photon fluorescence imaging using a plasmonic colour filter array", Journal of Biophotonics, 2021.
- M. Weiss, M. Fang, Y. Altmann, M. G. Paff, A. Di Fulvio, "Effect of natural gamma background radiation on portal monitor radioisotope unmixing", Scientific Reports, 10, 6811, 2021.
- K. Craigie, E. M. Gauger, Y. Altmann, C. Bonato, "Resource-efficient adaptive Bayesian tracking of magnetic fields with a quantum sensor", J. Condens. Matter Phys., 2021. (Arxiv preprint).
- J. Lesouple, B. Pilastre, Y. Altmann, J.-Y. Tourneret, "Hypersphere fitting from noisy data using an EM Algorithm", IEEE Signal Processing Letters, 2021. (Associated technical report)
- M. Fang, Y. Altmann, D. Della Latta, M. Salvatori, A. Di Fulvio, "Quantitative imaging and automated fuel pin identification for passive Gamma emission tomography ", Scientific Reports, 11, 2442, 2021.
- Q. Legros, J. Tachella, R. Tobin, A. McCarthy,S. Meignen, G. S.Buller, Y. Altmann, S. McLaughlin, M. E. Davies, "Robust 3D reconstruction of dynamic scenes from single-photon lidar using Beta-divergences", IEEE Trans. Image Processing, vol. 30, 2020. (Arxiv preprint)
- J. Rapp, C. Saunders, J. Tachella, J.Murray-Bruce, Y. Altmann, J.-Y. Tourneret, S. McLaughlin, R. Dawson, F. Wong, V. Goyal, "Seeing around corners with edge-resolved transient imaging", Nature Communications, 11, 5929, 2020.
- J. Howell, T. Hammarton, Y. Altmann, M. Jimenez, "High-speed particle detection and tracking in microfluidic devices using event-based sensing", Lab On A Chip, 20, 3024-3035, 2020.
- Q. Legros, S. Meignen, S. McLaughlin, Y. Altmann, "Expectation-Maximization based approach to 3D reconstruction from single-waveform multispectral Lidar data", IEEE Trans. Computational Imaging, vol. 6, 2020. (Arxiv preprint)
- Y. D. Shah, P. W. R. Connolly, J. P. Grant, D. Hao, C. Accarino, X. Ren, M. Kenney, V. Annese, K. G. Rew, Z. M. Greener, Y. Altmann, D. Faccio, G. S. Buller, D. R. S. Cumming, "Ultralow light level color image reconstruction using high-efficiency plasmonic metasurface mosaic filters", Optica, vol. 6, no. 6, 2020.
- J. Rapp, J. Tachella, Y. Altmann, S. McLaughlin, V. K. Goyal, "Advances in single-photon Lidar for autonomous vehicles", in IEEE Signal Processing Magazine, vol. 37, no. 4, 2020.
- Y. Altmann, A. Di Fulvio, M. G. Paff, S. D. Clarke, M. E. Davies, S. McLaughlin, A. O. Hero, S. A. Pozzi, "Expectation-Propagation for weak radionuclide identification at radiation portal monitors", Scientific Reports, 10, 6811, 2020.
- Y. Altmann, S. McLaughlin, M. E. Davies, "Fast online 3D reconstruction of dynamic scenes from individual single-photon detection events", IEEE Trans. Image processing, vol. 29, 2019. (Arxiv preprint)
- J. Tachella, Y. Altmann, N. Mellado, A. McCarthy, R. Tobin, G. S. Buller, J.-Y. Tourneret, S. McLaughlin, "Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers", Nature Communications,10, 4984, 2019. (Arxiv preprint)
- H. Zhu, Y. Altmann, A. Di Fulvio, S. McLaughlin, S. A. Pozzi, A. O. Hero, "A hierarchical Bayesian approach to neutron unfolding with organic scintillators", IEEE Trans. Nuclear Science, vol. 66, no. 10, 2019. (Arxiv preprint)
- J. Tachella, Y. Altmann, M. Márquez, H. Arguello-Fuentes, J.-Y. Tourneret, S. McLaughlin, "Bayesian 3D reconstruction of subsampled multispectral single-photon Lidar signals", IEEE Trans. Computational Imaging, vol. 6, 2019. (Arxiv preprint)
- G. Musarra, A. Lyons, E. Conca, Y. Altmann, F. Villa, F. Zappa, M.J. Padgett, D. Faccio, "Non-Line-of-Sight Three-Dimensional Imaging with a Single-Pixel Camera", Phys. Rev. Applied 12, 011002, 2019.
- A. K. Eldaly, Y. Altmann, A. Akram, P. McCool, K. Dhaliwal, S. McLaughlin, "Bayesian bacterial detection using irregularly sampled optical endomicroscopy images", Medical Image Analysis, vol. 57, 2019.
- S. Meignen, Q. Legros, Y. Altmann, S. McLaughlin, "A Novel Algorithm for the Identification of Dirac Impulses from Filtered Noisy Measurements", Signal Processing, vol. 162, pp. 268-281, Sept. 2019.
- J. Tachella, Y. Altmann, X. Ren, A. McCarthy, G. S. Buller, S. McLaughlin, J-Y Tourneret, "Bayesian 3D reconstruction of complex scenes from single-photon Lidar data", SIAM J. Imaging Sci., vol. 12, no. 1, 2019. Video.
- X. Ren, Y. Altmann, R. Tobin, A. McCarthy, S. McLaughlin, G. S. Buller, "Wavelength-time coding for multispectral 3D imaging using single-photon Lidar", Optics Express, vol. 26, no. 23, 2018.
- M. Paff, A. Di Fulvio, Y. Altmann, S. D. Clarke, A. O. Hero, S. A. Pozzi, "Identification of mixed sources with an organic scintillator-based radiation portal monitor", Journal of Nuclear Materials Management, vol. 46, no. 4, 2018.
- Y. Altmann, S. McLaughlin, M. J. Padgett, V. K Goyal, A. O. Hero, D. Faccio, "Quantum-inspired computational imaging", Science 361, 660, 2018.
- H. Wendt, S. Combrexelle, Y. Altmann, J-Y. Tourneret, S. McLaughlin, P. Abry, "Multifractal Analysis of Multivariate Images Using Gamma Markov Random Field Priors", SIAM Journal on Imaging Sciences, vol. 11, no. 2, 2018.
- P. Caramazza, K. Wilson, G. Gariepy, J. Leach, S. McLaughlin, D. Faccio, Y. Altmann, "Enhancing the recovery of temporal sequence of images using joint deconvolution", Scientific Reports 8, 5257, 2018.
- Y. Altmann, A. Maccarone, A. McCarthy, S. McLaughlin, G. S. Buller, "Spectral classification of sparse photon depth images", Optics Express, vol. 26, no.5, 2018.
- A. K. Eldaly, Y.Altmann, A. Perperidis, N. Krstajic, T. R. Choudhary, K.Dhaliwal, Stephen McLaughlin, "Deconvolution and restoration of optical endomicroscopy images", IEEE Trans. Computational Imaging, vol. 4, no. 2, June 2018 (Preprint available on arXiv).
- X. Ren, P. Connolly, A. Halimi, Y. Altmann, S. McLaughlin, I. Gyongy, R. K. Henderson, G. S. Buller, "High-resolution depth profiling using a range-gated Si CMOS SPAD quanta image sensor", Optics Express, vol. 26, no.5, 2018.
- A. Perperidis, H. E. Parker, A. Karam-Eldaly, Y. Altmann, K. Dhaliwal, R. R. Thomson, M.G. Tanner, S. McLaughlin, "Characterization and modelling of inter-core coupling in coherent fiber bundles", Optics Express, vol. 25, no. 10, 2017.
- R. E. Warburton, C. Aniculaesei, M. Clerici, Y. Altmann, G. Gariepy, D. T. Reid, S. McLaughlin, M. Petrovich, J. Hayes, R. K. Henderson, D. F. A. Faccio, J. Leach, "Observation of laser pulse propagation in optical fibers with a SPAD camera", Scientific Reports 7, 43302, 2017.
- R. Tobin, Y. Altmann, X. Ren, A. McCarthy, R. Lamb, S. McLaughlin, G. S. Buller, "Comparative study of sampling strategies for sparse photon multispectral Lidar imaging: towards mosaic filter arrays", Journal of Optics, vol. 19, no. 9, Aug. 2017.
- Y. Altmann, R. Aspden, M. Padgett, S. McLaughlin, "A Bayesian approach to denoising of single-photon binary images", IEEE Trans. Computational Imaging, vol. 3, no. 3, 2017. (Preprint available on arXiv).
- S. Chan, R. Warburton, G. Gariepy, Y. Altmann, S. McLaughlin, J. Leach, D. Faccio, "Fast tracking of hidden objects with single-pixel detectors", Electronics Letters, vol. 53, no. 15, 2017.
- A. Perperidis, A. Akram, Y. Altmann, P. McCool, J. Westerfeld, D. Wilson, K. Dhaliwal, S. McLaughlin, "Automated detection of uninformative frames in pulmonary optical endomicroscopy (OEM)", IEEE Trans. Biomedical Engineering, vol. 64, no. 1, 2017.
- Y. Altmann, A. Maccarone, A. McCarthy, G. Newstadt, G. S. Buller, S. McLaughlin, A. Hero, "Robust spectral unmixing of sparse multispectral Lidar waveforms using gamma Markov random fields", IEEE Trans. Computational Imaging, vol.3, no.4, Dec 2017.
- Y. Altmann, X. Ren, A. McCarthy, G. S. Buller, S. McLaughlin, "Robust Bayesian target detection algorithm for depth imaging from sparse single-photon data", IEEE Trans. Computational Imaging, vol. 2, no. 4, 2016. (Preprint available on arXiv)
- Y. Altmann, X. Ren, A. McCarthy, G. S. Buller, S. McLaughlin, "Lidar waveform based analysis of depth images constructed using sparse single photon data", IEEE Trans. Image Processing, vol. 25, no. 5, May 2016. (Preprint available on arXiv)
- Y. Altmann, M. Pereyra, J.Bioucas-Dias, "Collaborative sparse regression using spatially correlated supports - Application to hyperspectral unmixing", IEEE Trans. Image Processing, vol. 24, no. 12, pp 5800-5811, Dec. 2015. (Preprint available on arXiv)
- Y. Altmann, M. Pereyra, S. McLaughlin, "Bayesian nonlinear hyperspectral unmixing with spatial residual component analysis", IEEE Trans. Computational Imaging, vol. 1, no. 3, pp 174-185, Sept. 2015. (Preprint available on arXiv)
- Y. Altmann, S. McLaughlin, A. Hero, "Robust linear spectral unmixing using anomaly detection", IEEE Trans. Computational Imaging, vol. 1, no. 2, pp 74-85, June 2015. (Preprint available on arXiv)
- Y. Altmann, A. Wallace, S. McLaughlin, "Spectral unmixing of Multispectral signals", IEEE Trans. Signal Process., vol. 63, no. 20, pp. 5525-5534, Oct. 2015. (Preprint available on arXiv)
- N. Dobigeon, L. Tits, B. Somers, Y. Altmann and P. Coppin, "A comparison of nonlinear mixing models for vegetated areas using simulated and real hyperspectral data," IEEE J. Sel. Topics Applied Earth Observations and Remote Sensing, 2014, vol. 7, no. 6, pp. 1869-1878, June 2014
- Y. Altmann, N. Dobigeon and J.-Y. Tourneret, "Unsupervised post-nonlinear unmixing of hyperspectral images using a Hamiltonian Monte Carlo algorithm," IEEE Trans. Image Processing, vol. 23, no. 6, pp. 2663-2675, June 2014.
- Y. Altmann, N. Dobigeon, S. McLaughlin and J.-Y. Tourneret, "Residual component analysis of hyperspectral images - Application to joint nonlinear unmixing and nonlinearity detection," IEEE Trans. Image Processing, vol. 23, no. 5, pp. 2148-2158, May 2014.
- Y. Altmann, N. Dobigeon , S. McLaughlin and J.-Y. Tourneret, "Nonlinear spectral unmixing of hyperspectral images using Gaussian processes," IEEE Trans. Signal Processing, vol. 61, no. 10, pp. 2442-2453, May 2013.
- Y. Altmann, N. Dobigeon and J.-Y. Tourneret, "Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model," IEEE Trans. Image Processing, vol. 22, no. 4, pp. 1267-1276, Apr. 2013.
- Y. Altmann, A. Halimi, N. Dobigeon and J.-Y. Tourneret, "Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery," IEEE Trans. Image Processing, vol. 21, no. 6, pp. 3017-3025, June 2012.
- A. Halimi, Y. Altmann, N. Dobigeon and J.-Y. Tourneret, "Nonlinear unmixing of hyperspectral images using a generalized bilinear model," IEEE Trans. Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4153-4162, Nov. 2011.
Book chapters
- N. Dobigeon, Y. Altmann, N. Brun and S. Moussaoui, "Linear and nonlinear unmixing in hyperspectral imaging," in Resolving spectral mixtures - With application from ultrafast time-resolved spectroscopy to superresolution imaging, C. Ruckebusch , Ed. Oxford, U.K.: Elsevier, Data Handling in Science and Technology Series, 2016.
International conference papers
- D. Shen, S. McLaughlin, Y. Altmann, "Expectation-Propagation with Low-Rank Constraints for Linear Inverse Problems", Proc. European Signal Processing Conf. (EUSIPCO) 2023, to appear.
- A. Abdulaziz, M. E. Davies, Y. Altmann, S. McLaughlin, "Investigation of an end-to-end neural architecture for image-based source term estimation", Sensor Signal Processing for Defence (SSPD) Conference 2023, to appear.
- D. Yao, S. McLaughlin, Y. Altmann, "Unsupervised Expectation Propagation Method for Large-Scale Sparse Linear Inverse Problems", Sensor Signal Processing for Defence (SSPD) Conference 2022.
- K. Drummond, D. Yao, A. Pawlikowska, R. Lamb, S. McLaughlin, Y. Altmann, "Efficient joint surface detection and depth estimation of single-photon Lidar data using assumed density filtering", Sensor Signal Processing for Defence (SSPD) Conference 2022.
- J. M. Charsley, M. Rutkauskas, Y. Altmann, M. Botticelli, V. Risdonne, M. Smith, T. Visser, C. R. T. Young, and D. T. Reid, "Fast Mid-Infrared Spectroscopic Imaging for Painted Cultural Heritage," in Imaging and Applied Optics Congress 2022.
- D. Yao, Y. Altmann, S. McLaughlin, "Color image restoration in the low-photon count regime using Expectation-Propagation", IEEE ICIP 2022.
- Y. Altmann, "On approximate Bayesian methods for large-scale linear inverse problems", Proc. European Signal Processing Conf. (EUSIPCO) 2022.
- A. Abdulaziz, J. Zhou, A. Di Fulvio, Y. Altmann, S. McLaughlin, "Semi-supervised Gaussian Mixture Variational Autoencoder for Pulse Shape Discrimination", in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Singapore, May 2022.
- K. Drummond, A. Pawlikovska, R. Lamb, S. McLaughlin, Y. Altmann, "Joint surface detection and depth estimation using from single-photon data using ensemble estimatiors", Sensor Signal Processing for Defence (SSPD) Conference 2021, 2021.
- C. Saunders, W. Krska, J. Tachella, S. Seidel, J. Rapp, J. Murray-Bruce, Y. Altmann, S. McLaughlin, V. Goyal, "Edge-Resolved Transient Imaging: Performance Analyses, Optimizations, and Simulations", IEEE ICIP 2021.
- J. Lesouple, B. Pilastre, Y. Altmann, J.-Y. Tourneret, "Robust Hypersphere Fitting from Noisy Data Using an EM Algorithm", Proc. European Signal Processing Conf. (EUSIPCO) 2021.
- A. Abdulaziz, D. Yao, Y. Altmann, S. McLaughlin, "Blind deconvolution of images corrupted by Gaussian noise using Expectation Propagation", Proc. European Signal Processing Conf. (EUSIPCO) 2021.
- Z. Li, Y. Altmann, J. Chen, S. Mclaughlin, S. Rahardja, "Sparse Spectral Unmixing of Hyperspectral Images using Expectation-Propagation", VCIP 2020.
- Q. Legros, S. Meignen, M. E. Davies, S. McLaughlin, Y. Altmann,"Robust depth imaging in adverse scenarios using single-photon Lidar and beta-divergences", Sensor Signal Processing for Defence (SSPD) Conference 2020.
- Q. Legros, S. Meignen, S. McLaughlin, Y. Altmann, "Stochastic EM algorithm for fast analysis of single waveform multi-spectral Lidar data'', Proc. European Signal Processing Conf. (EUSIPCO) 2020.
- D. Yao, Y. Altmann, S. McLaughlin, M. E. Davies, "Joint robust linear regression and anomaly detection in Poisson noise using Expectation-Propagation", Proc. European Signal Processing Conf. (EUSIPCO) 2020.
- J. Tachella, Y. Altmann, J.-Y. Tourneret, S. McLaughlin, "Real-time 3D color imaging with single-photon Lidar data", IEEE CAMSAP, Guadeloupe, Dec. 2019.
- Y. Altmann, D. Yao, S. McLaughlin, M. E. Davies, "Robust linear regression and anomaly detection in the presence of Poisson noise using Expectation-Propagation", WCCM 2019, Singapore, Dec. 2019.
- J. Tachella, Y. Altmann, J.-Y. Tourneret, S. McLaughlin, "Fast surface detection in single-photon Lidar waveforms", Proc. European Signal Processing Conf. (EUSIPCO), A coruna, Spain, Sept. 2019.
- J. Tachella, Y. Altmann, J.-Y. Tourneret, S. McLaughlin, "On fast surface detection in single-photon Lidar waveforms", Proc. SPIE 11138, Wavelets and Sparsity XVIII, 111380T (9 September 2019).
- Y. Altmann, A. Perelli, M. E. Davies, "Expectation-Propagation algorithms for linear regression with Poisson noise: application to photon-limited spectral unmixing", in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019.
- J. Tachella, Y. Altmann, J.-Y. Tourneret, S. McLaughlin, "3D reconstruction using single-photon Lidar data exploiting the widths of the returns", in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Brighton, UK, May 2019.
- A. K. Eldaly, Y. Altmann, A. Akram, A. Perperidis, K. Dhaliwal, S. McLaughlin, "Patch-based sparse representation for bacterial detection", IEEE Intern. Symp. on Med. Imaging (ISBI), Venice, Italy, Apr. 2019.
- C. Chenot, M. Yaghoobi, M. E. Davies, Y. Altmann, "Anomaly detection with high resolution hyperspectral observations", IEEE Global Conference on Signal and Info. Process. (GlobalSIP), Anaheim, California, Nov. 2018.
- J. Tachella, Y. Altmann, M. Pereyra, J-Y Tourneret, "Bayesian restoration of high-dimensional photon-starved images", Proc. European Signal Processing Conf. (EUSIPCO), Rome, Italy, Sept. 2018.
- Y. Altmann, S. McLaughlin, "Range Estimation from Single-Photon Lidar Data Using a Stochastic EM Approach", Proc. European Signal Processing Conf. (EUSIPCO), Rome, Italy, Sept. 2018.
- A. K. Eldaly, Y.Altmann, A. Perperidis, Stephen McLaughlin, "Deconvolution of irregularly subsampled images", IEEE Workshop on Statistical Signal Processing (SSP) 2018.
- Y. Altmann, M. Padgett, S. McLaughlin, "Unsupervised Restoration of Subsampled Images Constructed from Geometric and Binomial data", IEEE CAMSAP, Curacao, Dec. 2017.
- A. Halimi, P. Connolly, X. Ren, I. Gyongy, R. K. Henderson,. S. McLaughlin, G. S. Buller, "Restoration of Depth and Intensity Images using a Graph Laplacian Regularization", IEEE CAMSAP, Curacao, Dec. 2017.
- Y. Altmann, R. Tobin, A. Maccarone, X. Ren, A. McCarthy, G. S. Buller and S. McLaughlin, “Bayesian restoration of reflectivity and range profiles from subsampled single-photon multispectral Lidar data,” Proc. European Signal Processing Conf. (EUSIPCO), Kos, Greece, Sept. 2017.
- M. Paff, A. Di Fulvio, Y. Altmann, S. D. Clarke, S. A. Pozzi, "Identification of mixed sources with an organic scintillator-based radiation portal monitor", Institute of Nuclear Materials Management 58th Annual Meeting, Indian Wells, July 2017.
- Y. Altmann, A. Maccarone, A. Halimi, A. McCarthy, G. S. Buller, S. McLaughlin, “Efficient range estimation and material quantification from multispectral Lidar waveforms,” Sensor Signal Processing for Defence (SSPD) Conference, Edinburgh, U.K., Sept. 2016.
- A. Halimi, Y. Altmann, A. McCarthy, X. Ren,R.Tobin, G. S. Buller, S. McLaughlin, “Robust unmixing algorithms for hyperspectral imagery,” Sensor Signal Processing for Defence (SSPD) Conference, Edinburgh, U.K., Sept. 2016.
- S. Combrexelle, H. Wendt, Y. Altmann, J-Y Tourneret, S. McLaughlin, P. Abry, "Bayesian joint estimation of the multifractality parameter of image patches using gamma Markov random field priors", IEEE Intern. Conf. in Image Process. (ICIP), Phoenix, Arizona, Sept. 2016.
- Y. Altmann, A. Maccarone, A. McCarthy, G. S. Buller, S. Mclaughlin, "Joint spectral clustering and range estimation for 3D scene reconstruction using multispectral Lidar waveforms'", Proc. European Signal Processing Conf. (EUSIPCO), Budapest, Hungary, Sept. 2016.
- A. Halimi, Y. Altmann, A. McCarthy, X. Ren, R. Tobin, G. S. Buller, S. Mclaughlin, "Restoration of Intensity and Depth images Constructed Using Sparse Single-Photon Data", Proc. European Signal Processing Conf. (EUSIPCO), Budapest, Hungary, Sept. 2016.
- S. Combrexelle, H. Wendt, Y. Altmann, J-Y Tourneret, S. McLaughlin, P. Abry, "'Bayesian estimation for the local assessment of the multifractality parameter of multivariate time series", Proc. European Signal Processing Conf. (EUSIPCO), Budapest, Hungary, Sept. 2016. Note: Best paper award.
- Y. Altmann, A. Maccarone, A. McCarthy, G. Newstadt, G. S. Buller, S. Mclaughlin, A. Hero, "Robust spectral unmixing of multispectral
Lidar waveforms", IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS), Los Angeles, California, August 2016. - P. McCool, Y. Altmann, A. Perperidis, Steve McLaughlin, "Robust Markov Random Field Outlier Detection and Removal in Subsampled Images", IEEE Workshop on Statistical Signal Processing (SSP), Palma de Mallorca, Spain, June 2016.
- Y. Altmann, A. Maccarone, A. McCarthy, G. Buller, S. McLaughlin, "Joint range estimation and spectral classification for 3D scene reconstruction using multispectral Lidar waveforms", IEEE Workshop on Statistical Signal Processing (SSP), Palma de Mallorca, Spain, June 2016.
- S. Combrexelle, H. Wendt, J.-Y. Tourneret, Y. Altmann, S. McLaughlin, P. Abry, "A Bayesian Approach for the Multifractal Analysis of Spatio-Temporal Data," Int. Conf. Systems, Signals and Image Process. (IWSSIP), Bratislava, Slovakia, May 2016.
- Y. Altmann, X. Ren, A. McCarthy, G. S. Buller, S. McLaughlin, "Target detection for depth imaging using sparse single-photon data", in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Shanghai, China, April 2016. Related technical report
- S. Combrexelle, H. Wendt, Y. Altmann, J.-Y. Tourneret, S. McLaughlin, P. Abry, "A Bayesian framework for the multifractal analysis of images using data augmentation and a Whittle approximation," in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Shanghai,
China, April 2016. - Y. Altmann, M. Pereyra, S. McLaughlin, "Nonlinear Spectral Unmixing Using Residual Component Analysis and a Gamma Markov Random Field", IEEE CAMSAP, Cancun, Mexico, Dec. 2015.
- Y.Altmann, M. Pereyra and J.Bioucas-Dias, "Linear spectral unmixing using collaborative sparse regression and correlated supports," IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS), Tokyo, Japan, June 2015.
- Y.Altmann, S. McLaughlin and A. Hero, "Robust Linear Spectral Unmixing using Outlier detection", in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), 2015.
- Y.Altmann and S. McLaughlin, “Nonlinear Spectral unmixing of hyperspectral images using Residual Component Analysis,”Sensor Signal Processing for Defence (SSPD) Conference, Edinburgh, U.K., Sept. 2014.
- Y. Altmann, S.McLaughlin and N. Dobigeon, "Sampling from a Gaussian distribution truncated on a simplex: A review," IEEE Workshop on Statistical Signal Processing (SSP), Gold Coast, Australia, June 2014.
- N. Dobigeon, L. Tits, B. Somers, Y. Altmann and P. Coppin, "Nonlinear unmixing of vegetated areas: a model comparison based on simulated and real hyperspectral data," in Proc. IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS), Lausanne, Switzerland, June 2014.
- Y. Altmann, N. Dobigeon, S. McLaughlin and J.-Y. Tourneret, "Residual component analysis of hyperspectral images for joint nonlinear unmixing and nonlinearity detection," in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Florence, Italy, May 2014.
- Y. Altmann, N. Dobigeon , and J.-Y. Tourneret, "Bayesian algorithm for unsupervised unmixing of hyperspectral images using a post-nonlinear model," Proc. European Signal Processing Conf. (EUSIPCO), Marrakech, Marroco, Sept. 2013.
- Y. Altmann, N. Dobigeon, J.-Y. Tourneret and S. McLaughlin, "Nonlinear hyperspectral unmixing using Gaussian processes," IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS), Gainesville, FL, June 2013. Note: Best Paper Award
- Y. Altmann, N. Dobigeon, J.-Y. Tourneret and J. C. M. Bermudez, "A robust test for nonlinear mixture detection in hyperspectral images," in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Vancouver, Canada, 2013, to appear.
- Y. Altmann, N. Dobigeon and J.-Y. Tourneret , "Detecting nonlinear mixtures in hyperspectral images," IEEE GRSS Workshop on Hyperspectral Image and SIgnal Processing: Evolution in Remote Sensing (WHISPERS), Shangai, China, June 2012.
- Y. Altmann, N. Dobigeon, S. McLaughlin and J.-Y. Tourneret, "Nonlinear unmixing of hyperspectral images using Gaussian processes," in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Kyoto, Japan, March 2012, pp. 1249-1252.
- Y. Altmann, N. Dobigeon, S. McLaughlin and J.-Y. Tourneret , "Nonlinear unmixing of hyperspectral images using radial basis functions and orthogonal least squares", IEEE Int.Geoscience and Remote Sensing Symp. (IGARSS), Vancouver, Canada, July 2011, pp. 1151-1154.
- Y. Altmann, A. Halimi, N. Dobigeon and J.-Y. Tourneret , "A post nonlinear mixing model for hyperspectral images unmixing", IEEE Int.Geoscience and Remote Sensing Symp. (IGARSS), Vancouver, Canada, July 2011, pp. 1882-1885.
- A. Halimi, Y. Altmann, N. Dobigeon, and J.-Y. Tourneret, "Unmixing hyperspectral images using the generalized bilinear model," in Proc. IEEE Int. Geosci. Remote Sens. Symp. (IGARSS), Vancouver, Canada, July 2011, pp. 1886-1889.
- A. Halimi, Y. Altmann, N. Dobigeon and J.-Y. Tourneret, "Nonlinear unmixing of hyperspectral images using a generalized bilinear model," IEEE Workshop on Statistical Signal Processing (SSP), Nice, France, June 2011, pp. 413-416.
- Y. Altmann, N. Dobigeon and J.-Y. Tourneret , "Bilinear models for nonlinear unmixing of hyperspectral images ", IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lisbon, Portugal, June 2011, pp. 1-4.
- Y. Altmann, A. Halimi, N. Dobigeon and J.-Y. Tourneret, "Supervised nonlinear spectral unmixing using a polynomial post nonlinear model for hyperspectral imagery," IEEE Int. Conf. Acoust., Speech, and Signal Processing (ICASSP), Prague, Czech Republic, May 2011, pp. 1009-1012.
- J. Lesouple, B. Pilastre, Y. Altmann, J.-Y. Tourneret, "Estimation du centre et du rayon d'une hypersphère à l'aide d'une loi a priori de Von Mises-Fisher et d'un algorithme EM", Actes du XXIXVIIIième Colloque GRETSI, Nancy, France, Aug. 2022, in French, to appear.
- J.-F. Giovannelli, Y. Altmann, "Segmentation bayesienne d'images constantes par morceaux: cas de distorsion non-linéaire, données manquantes et bruit de Poisson", Actes du XXVIIième Colloque GRETSI, Lille, France, Aug. 2019, in French.
- Y. Altmann, N. Dobigeon, Steve McLaughlin and J.-Y. Tourneret, "Démélange non linéaire d'images hyperspectrales à l'aide de fonctions radiales de base et de moindres carrés orthogonaux," Actes du XXIIIième Colloque GRETSI, Bordeaux, France, Sept. 2011, in French.
Theses
- Y. Altmann, "Nonlinear unmixing of hyperspectral images," PhD. Thesis, INP TOULOUSE, October 2013