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2. Re-ordering of Hadamard matrix using Fourier transform and gray-level co-occurrence matrix for compressive single-pixel imaging

Author

Vaz, Pedro G., Gaudêncio, Andreia, Ferreira, L. F. Requicha, Humeau-Heurtier, Anne, Morgado, Miguel, and Cardoso, João

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Instrumentation and Detectors
Abstract

One of the most active research fields in single-pixel imaging is the influence of the sampling basis and its order in the quality of the reconstructed images. This paper presents two new orders, ascending scale (AS) and ascending inertia (AI), of the Hadamard basis and test their performance, using simulation and experimental methods, for low sampling ratios (0.5 to 0.01). These orders were compared with two state-of-the-art orders, cake-cutting (CC) and total gradient (TG), using TVAL3 as the reconstruction algorithm and three noise levels. These newly proposed orders have better reconstructed image quality on the simulation data set (110 images) and achieved structure similarity index values higher than CC order. The experimental data set (2 images) showed that the AS and AI orders performed better with a sampling ratio of 0.5, while for lower sampling ratio the performance of AS, AI and CC was similar. The TG order performed worst in the majority of the cases. Finally, the simulation results present clear evidence that peak signal-to-noise ratio (PSNR) is not a reliable image quality assessment (IQA) metric to assess image reconstruction quality in the context of single pixel imaging.

Published
2022

14. Multiscale Entropy Approaches and Their Applications.

Author

Humeau-Heurtier, Anne and Humeau-Heurtier, Anne

Subjects
History of engineering & technology, Alzheimer disease, CPD, Cramér-Rao Lower Bound, EEG, Fisher ratio, HMSVM, HRV, Holter, ICEEMDAN, Multiscale Permutation Entropy, PD, RCMDE, RR interval, SVM, Voronoi decomposition, Wikipedia, aging, ambient temperature, approximate entropy, asynchrony, bearing fault diagnosis, biometric characterization, brain complexity, cardiac autonomic neuropathy, cardiac risk stratification, center of pressure, clock drawing test, complexity, composite cross-sample entropy, consolidation, copula density, corsi block tapping test, coupling, cross-approximate entropy, cross-conditional entropy, cross-distribution entropy, cross-entropy, cross-fuzzy entropy, cross-sample entropy, default mode network, dependency structures, diabetes, digit span test, dynamic functional connectivity, edge complexity, electrocardiogram, electroencephalogram, embodied media, ensemble empirical mode decomposition, entropy, entropy rate, episodic memory, estimator variance, eye movement events detection, fMRI, falls, fault diagnosis, financial time series, finite-length signals, fluid intelligence, functional near infra-red spectroscopy, fuzzy entropy, gait, heart rate variability, heart rate variability (HRV), heart sound, human behavior, humanoid, local robust principal component analysis, long term monitoring, magnetoencephalogram, medical information, memory effect, mental workload, missing values, motif, multi-component signal, multi-scale, multi-scale dispersion entropy, multi-scale entropy, multi-scale entropy (MSE), multi-scale permutation entropy, multifractal spectrum, multilevel entropy map, multiscale analysis, multiscale cross-entropy, multiscale distribution entropy, multiscale entropy, multiscale indices, multiscale time irreversibility, multivariate data, multivariate multiscale dispersion entropy, multivariate time series, network complexity, node complexity, nonlinear analysis time series analysis, nonlinear dynamics, ordinal patterns, page view, permutation entropy, physiological data, postural control, postural stability index, predictability, prefrontal cortex, preterm neonate, pulse interval, resting state, resting-state functional magnetic resonance imaging, sample entropy, short-term inter-beat interval, signal complexity, sleep staging, stability states, structural health monitoring, systolic arterial pressure (SAP), systolic blood pressure, tele-communication, telemetry, tensor decomposition, thermoregulation, time-scale decomposition, variational mode decomposition, vasopressin, vector autoregressive fractionally integrated (VARFI) models, weak fault
Abstract

Summary: Multiscale entropy (MSE) measures to evaluate the complexity of time series by taking into account the multiple time scales in physical systems were proposed in the early 2000s. Since then, these approaches have received a great deal of attention and have been used in a wide range of applications. Multivariate approaches have also been developed. The algorithms for an MSE approach are composed of two main steps: (i) a coarse-graining procedure to represent the system's dynamics on different scales and (ii) the entropy computation for the original signal and for the coarse-grained time series to evaluate the irregularity for each scale. Moreover, different entropy measures have been associated with the coarse-graining approach, each one having its advantages and drawbacks. In this Special Issue, we gathered 24 papers focusing on either the theory or applications of MSE approaches. These papers can be divided into two groups: papers that propose new developments in entropy-based measures or improve the understanding of existing ones (9 papers) and papers that propose new applications of existing entropy-based measures (14 papers). Moreover, one paper presents a review of cross-entropy methods and their multiscale approaches.

17. Characterization of Home-Acquired Blood Pressure Time Series Using Multiscale Entropy for Patients Treated Against Kidney Cancer

Author

Jamin, Antoine, Fasquel, Jean-Baptiste, Humeau-Heurtier, Anne, Abraham, Pierre, Leftheriotis, Georges, Henni, Samir, Akan, Ozgur, Series Editor, Bellavista, Paolo, Series Editor, Cao, Jiannong, Series Editor, Coulson, Geoffrey, Series Editor, Dressler, Falko, Series Editor, Ferrari, Domenico, Series Editor, Gerla, Mario, Series Editor, Kobayashi, Hisashi, Series Editor, Palazzo, Sergio, Series Editor, Sahni, Sartaj, Series Editor, Shen, Xuemin (Sherman), Series Editor, Stan, Mircea, Series Editor, Xiaohua, Jia, Series Editor, Zomaya, Albert Y., Series Editor, Ahmed, Mobyen Uddin, editor, Begum, Shahina, editor, and Fasquel, Jean-Baptiste, editor

Published
2018
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31. Evaluation of Systems’ Irregularity and Complexity : Sample Entropy, Its Derivatives, and Their Applications Across Scales and Disciplines

Author

Humeau-Heurtier, Anne

Abstract

Based on information theory, a number of entropy measures have been proposed since the 1990s to assess systems’ irregularity, such as approximate entropy, sample entropy, permutation entropy, intrinsic mode entropy, and dispersion entropy, to cite only a few. Among them, sample entropy has been used in a very large variety of disciplines for both univariate and multivariate data. However, improvements to the sample entropy algorithm are still being proposed because sample entropy is unstable for short time series, may be sensitive to parameter values, and can be too time-consuming for long data. At the same time, it is worth noting that sample entropy does not take into account the multiple temporal scales inherent in complex systems. It is maximized for completely random processes and is used only to quantify the irregularity of signals on a single scale. This is why analyses of irregularity—with sample entropy or its derivatives—at multiple time scales have been proposed to assess systems’ complexity. This Book presents contributions related to new and original research based on the use of sample entropy or its derivatives.

Published
2018

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