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Compressive Hyperspectral Imaging by Out-of-Focus Modulations and Fabry-Pérot Spectral Filters

Abstract: We describe a compressive hyperspectral imaging scheme that randomly convolves each spectral band of the data cube. This independent sensing of each wavelength relies on a tiling of Fabry-Pérot filters incorporated in the CMOS pixel grid.
2014 “Proceedings of the second “international Traveling Workshop on Interactions between Sparse models and Technology” (iTWIST'14)”
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Robust phase unwrapping by convex optimization

Abstract: The 2-D phase unwrapping problem aims at retrieving a “phase” image from its modulo 2π observations. Many applications, such as interferometry or synthetic aperture radar imaging, are concerned by this problem since they proceed by recording complex or modulated data from which a “wrapped” phase is extracted.
2014 Image Processing (ICIP), 2014 IEEE International Conference on
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Bits of Images: Inverting Local Image Binary Descriptors

(print (nth 5 (org-heading-components))) Abstract: Local Binary Descriptors (LBDs) are good at matching image parts, but what information is actually carried? This question is usually masked by a comparison of matching performances.
2013 Bits of Images: Inverting Local Image Binary Descriptors
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Compressive Acquisition of Sparse Deflectometric Maps

Abstract: Schlieren deflectometry aims at measuring deflections of light rays from transparent objects, which is subsequently used to characterize the objects. With each location on a smooth object surface a sparse deflection map (or spectrum) is associated.
2013 Proceedings of the 10th International Conference on Sampling Theory and Applications (SampTA)
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Compressive Schlieren Deflectometry

Abstract: Schlieren deflectometry aims at characterizing the deflections undergone by refracted incident light rays at any surface point of a transparent object. For smooth surfaces, each surface location is actually associated with a sparse deflection map (or spectrum).
2013 Proceedings of ICASSP 2013
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Consistent Iterative Hard Thresholding for Signal Declipping

Abstract: Clipping or saturation in audio signals is a very common problem in signal processing, for which, in the severe case, there is still no satisfactory solution. In such case, there is a tremendous loss of information, and traditional methods fail to appropriately recover the signal.
2013 Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
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Quantized Iterative Hard Thresholding: Bridging 1-bit and High-Resolution Quantized Compressed Sensing

Abstract: In this work, we show that reconstructing a sparse signal from quantized compressive measurement can be achieved in an unified formalism whatever the (scalar) quantization resolution, i.e., from 1-bit to high resolution assumption.
2013 Proceedings of International Conference on Sampling Theory and Applications 2013, Bremen, Germany
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Iterative Hypothesis Testing for Multi-object Tracking with Noisy/Missing Appearance Features

Abstract: This paper assumes prior detections of multiple targets at each time instant, and uses a graph-based approach to connect those de- tections across time, based on their position and appearance estimates.
2012 11th Asian Conference on Computer Vision, Detection and Tracking in Challenging Environments Workshop, Daejeon, Korea, Lecture Notes in Computer Science, Vol. 7724-7727
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Sparsity-driven optical deflection tomography with non-linear light ray propagation

Abstract: Optical deflection tomography based on phase-shifting Schlieren is well adapted for three-dimensional imaging of objects with large refractive index variations. We propose a reconstruction algorithm that takes into account light refraction and spatial sparsity of the sample.
2012 Optimess 2012
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TV-$\ell_{2}$ Refractive Index Map Reconstruction from Polar Domain Deflectometry

2012 Proc. 1st international Traveling Workshop for Interacting Sparse models and Technology (iTWIST'12), Marseille, France
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