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Compressive Sampling Approach for Image Acquisition with Lensless Endoscope

Abstract: The lensless endoscope is a promising device designed to image tissues in vivo at the cellular scale. The traditional acquisition setup consists in raster scanning during which the focused light beam from the optical fiber illuminates sequentially each pixel of the field of view (FOV).
2018 Proceedings of iTWIST'18
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Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy

Abstract: Fourier Transform Interferometry (FTI) is an interferometric procedure for acquiring HyperSpectral (HS) data. Recently, it has been observed that the light source highlighting a (biologic) sample can be coded before the FTI acquisition in a procedure called Coded Illumination-FTI (CI-FTI).
2018 2018 25th IEEE International Conference on Image Processing (ICIP)
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Processing of binary fringe patterns obtained by phase-shifting time-averaged shearography on vibrating objects

Abstract: Shearography can be used for full-field strain measurements in the field of vibration analysis. It provides the spatial derivative of the optical phase difference of the vibration modes amplitude along the so-called shear direction.
2018
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Reference-less algorithm for circumstellar disks imaging

Abstract: Circumstellar disks play a key role in the understanding of stellar systems. Direct imaging of such extended structures is a challenging task. Current post-processing techniques, first tailored for exoplanets imaging, tend to produce deformed images of the circumstellar disks, hindering our capability to study their shape and photometry in details.
2018 Proceedings of iTWIST'18
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Taking the edge off quantization: projected back projection in dithered compressive sensing

Abstract: Quantized compressive sensing (QCS) deals with the problem of representing compressive signal measurements with finite precision representation, i.e., a mandatory process in any practical sensor design. To characterize the signal reconstruction quality in this framework, most of the existing theoretical analyses lie heavily on the quantization of sub-Gaussian random projections (e.
2018 IEEE
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A greedy blind calibration method for compressed sensing with unknown sensor gains

Abstract: The realisation of sensing modalities based on the principles of compressed sensing is often hindered by discrepancies between the mathematical model of its sensing operator, which is necessary during signal recovery, and its actual physical implementation, which can amply differ from the assumed model.
2017 Proceedings of IEEE International Symposium on Information Theory
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Compressive Hyperspectral Imaging using Coded Fourier Transform Interferometry

Abstract: Fourier Transform Interferometry (FTI) is a Hyperspectral (HS) imaging technique that is specially desirable in high spectral resolution applications, such as spectral microscopy in biology. The current resolution limit of FTI is actually due to the durability of biological elements when exposed to illuminating light.
2017 Proceedings of SPARS'17
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Fast Method to Fit a C1 Piecewise-Bézier Function to Manifold-Valued Data Points: How Suboptimal is the Curve Obtained on the Sphere S2?

Abstract: We propose an analysis of the quality of the fitting method proposed in Gousenbourger et al., 2017 (ESANN2017 proceedings). This method fits smooth paths to manifold-valued data points using C1 piecewise-Bézier functions.
2017 Geometric Science of Information. GSI 2017. Lecture Notes in Computer Science
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Piecewise-Bezier C1 smoothing on manifolds with application to wind field estimation

Abstract: We propose an algorithm for fitting C1 piecewise-Bezier curves to (possibly corrupted) data points on manifolds. The curve is chosen as a compromise between proximity to data points and regularity.
2017 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2017)
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Rare Eclipses in Quantised Random Embeddings of Disjoint Convex Sets: a Matter of Consistency?

Abstract: We study the problem of verifying when two disjoint closed convex sets remain separable after the application of a quantised random embedding, as a means to ensure exact classification from the signatures produced by this non-linear dimensionality reduction.
2017 Proceedings of SPARS'17
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