Search results for "Signal and Image processing"
showing 10 items of 454 documents
Echocardiographic reference ranges for normal non-invasive myocardial work indices: results from the EACVI NORRE study
2019
International audience; Aims - To obtain the normal ranges for 2D echocardiographic (2DE) indices of myocardial work (MW) from a large group of healthy volunteers over a wide range of ages and gender. Methods and results - A total of 226 (85 men, mean age: 45 ± 13 years) healthy subjects were enrolled at 22 collaborating institutions of the Normal Reference Ranges for Echocardiography (NORRE) study. Global work index (GWI), global constructive work (GCW), global work waste (GWW), and global work efficiency (GWE) were estimated from left ventricle (LV) pressure-strain loops. Peak LV systolic pressure was non-invasively derived from brachial artery cuff pressure. The lowest values of MW indic…
Wood fiber orientation assessment based on punctual laser beam excitation: A preliminary study
2016
International audience; The EU imposes standards for the use of wood in structural applications. Local singularities such as knots affect the wood mechanical properties. They can be revealed by looking at the wood fiber orientation. For this reason, many methods were proposed to estimate the orientation of wood fiber using optical means, X-rays, or scattering measurement techniques. In this paper, an approach to assess the wood fiber orientation based on thermal ellipsometry is developed. The wood part is punctually heated with a Nd-YAG Laser and the thermal response is acquired by an infrared camera. The thermal response is elliptical due to the propagation of the heat through and along th…
Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm
2013
International audience; We present in this paper the decomposition of human skin absorption spectra with a Non-negative Matrix Factorization method. In doing so, we are able to quantify the relative proportion of the main chromophores present in the epidermis and the dermis. We present experimental results showing that we obtain a good estimate of melanin and hemoglobin concentrations. Our approach has been validated by analyzing the human skin absorption spectra in areas of healthy skin and areas affected by melasma on eight patients.
A new strategy for effective learning in population Monte Carlo sampling
2016
In this work, we focus on advancing the theory and practice of a class of Monte Carlo methods, population Monte Carlo (PMC) sampling, for dealing with inference problems with static parameters. We devise a new method for efficient adaptive learning from past samples and weights to construct improved proposal functions. It is based on assuming that, at each iteration, there is an intermediate target and that this target is gradually getting closer to the true one. Computer simulations show and confirm the improvement of the proposed strategy compared to the traditional PMC method on a simple considered scenario.
Anti-tempered Layered Adaptive Importance Sampling
2017
Monte Carlo (MC) methods are widely used for Bayesian inference in signal processing, machine learning and statistics. In this work, we introduce an adaptive importance sampler which mixes together the benefits of the Importance Sampling (IS) and Markov Chain Monte Carlo (MCMC) approaches. Different parallel MCMC chains provide the location parameters of the proposal probability density functions (pdfs) used in an IS method. The MCMC algorithms consider a tempered version of the posterior distribution as invariant density. We also provide an exhaustive theoretical support explaining why, in the presented technique, even an anti-tempering strategy (reducing the scaling of the posterior) can …
Analysis of human skin hyper-spectral images by non-negative matrix factorization
2011
International audience; This article presents the use of Non-negative Matrix Factorization, a blind source separation algorithm, for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The evaluated spectra come from a Hyper-Spectral Image, which is the result of the processing of a Multi-Spectral Image by a neural network-based algorithm. The implemented source separation algorithm is based on a multiplicative coeffi cient upload. The goal is to represent a given spectrum as the weighted sum of two spectral components. The resulting weighted coefficients are used to quantify melanin and hemoglobin content in the given spectra. Results present a …
Subsignal-based denoising from piecewise linear or constant signal
2011
15 pages; International audience; n the present work, a novel signal denoising technique for piecewise constant or linear signals is presented termed as "signal split." The proposed method separates the sharp edges or transitions from the noise elements by splitting the signal into different parts. Unlike many noise removal techniques, the method works only in the nonorthogonal domain. The new method utilizes Stein unbiased risk estimate (SURE) to split the signal, Lipschitz exponents to identify noise elements, and a polynomial fitting approach for the sub signal reconstruction. At the final stage, merging of all parts yield in the fully denoised signal at a very low computational cost. St…
Non Linear Image Restoration in Spatial Domain
2011
International audience; In the present work, a novel image restoration method from noisy data samples is presented. The restoration was per-formed by using some heuristic approach utilizing data samples and smoothness criteria in spatial domain. Unlike most existing techniques, this approach does not require prior modelling of either the image or noise statistics. The proposed method works in an interactive mode to find the best compromise between the data (mean square error) and the smoothing criteria. The method has been compared with the shrinkage approach, Wiener filter and Non Local Means algorithm as well. Experimental results showed that the proposed method gives better signal to noi…
Signal Restoration via a Splitting Approach
2012
International audience; In the present study, a novel signal restoration method from noisy data samples is presented and is termed as "signal split (SSplit)" approach. The new method utilizes Stein unbiased risk estimate estimator to split the signal, the Lipschitz exponents to identify noise elements and a heuristic approach for the signal reconstruction. However, unlike many noise removal techniques, the present method works only in the non-orthogonal domain. Signal restoration was performed on each individual part by finding the best compromise between the data samples and the smoothing criteria. Statistical results are quite promising and suggest better performance than the conventional…
Optical Flow with Theoretically Justified Warping Applied to Medical Imaging
2015
International audience; Motion induced artifacts represent a major obstacle in the correct malignant lesion detection in medical imaging especially in MRI. The goal of this paper is to evaluate the performance of a new non-rigid motion correction algorithm based on the optical flow method. The proposed algorithm specifically addresses three major problems in MRI: the induced gaps in 3D images, the constancy assumption of current optical flow algorithms and the existence of large non-linear movement. In this paper, we compare the performance of extracted kinetic features from the tumor regions under consideration of several 2-D or 3-D motion compensation parameters for the differential diagn…