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Improving the Correlation Lower Bound for Simultaneous Orthogonal Matching Pursuit

Abstract: The simultaneous orthogonal matching pursuit (SOMP) algorithm aims to find the joint support of a set of sparse signals acquired under a multiple measurement vector model. Critically, the analysis of SOMP depends on the maximal inner product of any atom of a suitable dictionary and the current signal residual, which is formed by the subtraction of previously selected atoms.
2016 IEEE Signal Processing Letters
DOI DIAL arXiv

Non-parametric PSF estimation from celestial transit solar images using blind deconvolution

Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the convolution of an ideal image with a Point Spread Function (PSF).
2016 Journal of Space Weather and Space Climate
DOI DIAL arXiv

On The Exact Recovery Condition of Simultaneous Orthogonal Matching Pursuit

Abstract: Several exact recovery criteria (ERC) ensuring that orthogonal matching pursuit (OMP) identifies the correct support of sparse signals have been developed in the last few years. These ERC rely on the restricted isometry property (RIP), the associated restricted isometry constant (RIC) and sometimes the restricted orthogonality constant (ROC).
2016 IEEE Signal Processing Letters
DOI DIAL arXiv

A Quantized Johnson Lindenstrauss Lemma: The Finding of Buffon's Needle

Abstract: In 1733, Georges-Louis Leclerc, Comte de Buffon in France, set the ground of geometric probability theory by defining an enlightening problem: What is the probability that a needle thrown randomly on a ground made of equispaced parallel strips lies on two of them?
2015 IEEE Transactions on Information Theory
DOI DIAL arXiv ipynb Demo

Compressive Imaging and Characterization of Sparse Light Deflection Maps

Abstract: Light rays incident on a transparent object of uniform refractive index undergo deflections, which uniquely characterize the surface geometry of the object. Associated with each point on the surface is a deflection map (or spectrum) which describes the pattern of deflections in various directions.
2015 SIAM Journal on Imaging Sciences
DOI DIAL arXiv

Quantitative characterization of biofunctionalization layers by robust image analysis for biosensor applications

Abstract: This work describes the development of a characterization method for biofunctionalized surfaces and its use for biosensor applications. The method is based on the processing of fluorescence images obtained by confocal microscopy.
2015 Sensors and Actuators B: Chemical : international journal devoted to research and development of physical and chemical transducers
DOI DIAL

Compressive optical deflectometric tomography: a constrained total-variation approach

Abstract: Optical Deflectometric Tomography (ODT) provides an accurate characterization of transparent materials whose complex surfaces present a real challenge for manufacture and control. In ODT, the refractive index map (RIM) of a transparent object is reconstructed by measuring light deflection under multiple orientations.
2014 Inverse Problems and Imaging
DOI DIAL arXiv

From bits to images: Inversion of local binary descriptors

Abstract: Local Binary Descriptors are becoming more and more popular for image matching tasks, especially when going mobile. While they are extensively studied in this context, their ability to carry enough information in order to infer the original image is seldom addressed.
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI DIAL arXiv

Heterogenous void growth revealed by in situ 3-D X-ray mocrotomography using automatic cavity tracking

Abstract: Ductile fracture by nucleation, growth and coalescence of internal voids is the dominant fracture mechanism in metals at ambient temperature. Micromechanics-based models for each elementary mechanism have been developed and enhanced over the past 40 years, allowing microstructure-informed failure predictions essentially assuming homogeneous damage evolution.
2014 Acta Materialia
DOI DIAL

Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors

Abstract: The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse signals. Practical ADCs not only sample but also quantize each measurement to a finite number of bits; moreover, there is an inverse relationship between the achievable sampling rate and the bit-depth.
2013 IEEE Transactions on Information Theory
Code DOI DIAL arXiv Demo