Image Processing for Space & Earth Observations
Multisource & Multispectral Image Processing via Bayesian Inference


André Jalobeanu
Research Scientist and Founder
BayesMap Solutions, LLC

Phone: +1 650 485-0059

Castro Valley, CA, USA

  • Who Am I?
  • Research Interests
  • Research Projects (PI)
  • ResearchGate Publications
  • Who Am I?

    I am a research scientist at BayesMap Solutions, LLC which I founded in Sep 2014. I provide topographic LiDAR consulting services on topics such as geometric correction, uncertainty prediction, change detection, full-waveform processing, ground filtering and gridding.

    From Nov 2012 to Jul 2014 I was a research fellow at ARL, UT Austin, and located at the Naval Postgraduate School in Monterey, CA, in the Remote Sensing Center. Before, I worked at CGE (University of Évora, Portugal) between 2008 and 2012 (hired within the Ciencia 2008 program of FCT), after 3 years with CNRS, France, in the MIV team at LSIIT near Strasbourg. Before, I was with RIACS at NASA Ames research center (California, USA) from Jan 2002 to Dec 2004, with an INRIA postdoc fellowship during 2002. During that period, I was part of the Bayesian Vision Group led by P. Cheeseman, where I worked on 3D surface reconstruction of asteroids, wavelets on meshes and surface modeling.

    Now my research projects include full-waveform topographic LiDAR data processing, ground filtering and gridding for DEM generation, and also photogrammetry, data fusion and super-resolution. My main area is data processing and analysis (images, signals, time series) through Bayesian inference, and one of the priorities is the propagation and the evaluation of uncertainties. My research is application-inspired, and so far it has been motivated by various inverse problems in remote sensing, planetary sciences, Earth sciences and astronomy. I am currently collaborating with F. Schmidt and C. Marmo (Univ. Paris Sud, France), C. Collet (LSIIT Illkirch, France), D. Fitzenz, C. Gama (CGE Evora, Portugal), G. Goncalves (U. Coimbra, Portugal), J. Goncalves (U. Porto, Portugal), S. Hickman (USGS Menlo Park, USA) and K. Knuth (Univ. of Albany, USA).

    Please visit my ResearchGate page for up-to-date information and publications.

    Educational Background

    All degrees are from the University of Nice-Sophia Antipolis (UNSA), France.

    Research Interests

    Keywords: Bayesian inference, data processing, LiDAR, computer vision, dense stereo, photogrammetry, DEM generation, data fusion, super-resolution, denoising, deconvolution

    Research topics & Applications I am interested in

    • Full-waveform LiDAR data processing for probabilistic digital terrain model generation (topography and vegetation)
    • Dense stereo disparity inference for topography and ground motion measurement
    • 3D Surface recovery from multiple images in planetary sciences
    • Data fusion and super-resolution for space and planetary sciences
    • Modeling natural images, terrains and small bodies, as well as various radiometric changes, for a better understanding and a more robust reconstruction
    • Estimating, simplifying, propagating uncertainties (3D reconstruction, rock compaction, recursive data fusion...)
    • Image denoising and deblurring remote sensing and astronomical images
    • Blind deconvolution for point spread function estimation

    Favorite Approaches & Methods

    • Forward modeling (physics-based generative models, inverse problem approach to image analysis)
    • Probability theory (Bayesian inference, graphical models, hidden variables, Markov Random Fields and trees)
    • Sampling and interpolation theories (as required by subpixel motion estimation)
    • Multiresolution analysis:
      • wavelet transforms in 2D (wavelet packets, complex wavelets),
      • wavelet transforms on subdivided triangular meshes, wavelet pyramids
    • Optimization techniques (deterministic and stochastic)
    • Geometry (image acquisition modeling)

    Research Projects (PI)

    AutoProbaDTM (2010-2012)

    • Title: Automated Probabilistic Digital Terrain Model generation from raw LiDAR data
    • Keywords: DEM generation, full waveform LiDAR, Bayesian inference, uncertainty, automated mapping
    • Funding: Fundacao para a Ciencia e a Tecnologia (FCT)
    • Budget: 140 kEUR
    • Website:

    SpaceFusion (2006-2008)

    • Title: Model-based image data fusion via Bayesian inference in astronomy and remote sensing
    • Keywords: Data fusion, Uncertainty, Error map, Bayesian inference, Sampling theory, DSM generation, Stereo vision, Disparity map, Camera calibration, Super-resolution, Pan-sharpening
    • Funding: Agence Nationale pour la Recherche (ANR) (Jeunes Chercheurs 2005)
    • Budget: 120 kEUR
    • Website:

    Selected Publications

    Webmaster (C. Collet), (M.Louys)
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