Search results for "noise reduction"
showing 10 items of 71 documents
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…
Total-variation methods for gravitational-wave denoising: Performance tests on Advanced LIGO data
2018
We assess total-variation methods to denoise gravitational-wave signals in real noise conditions, by injecting numerical-relativity waveforms from core-collapse supernovae and binary black hole mergers in data from the first observing run of Advanced LIGO. This work is an extension of our previous investigation where only Gaussian noise was used. Since the quality of the results depends on the regularization parameter of the model, we perform an heuristic search for the value that produces the best results. We discuss various approaches for the selection of this parameter, either based on the optimal, mean, or multiple values, and compare the results of the denoising upon these choices. Mor…
Automated detection and localization system of myocardial infarction in single-beat ECG using Dual-Q TQWT and wavelet packet tensor decomposition.
2019
Abstract Background and objective It is challenging to conduct real-time identification of myocardial infarction (MI) due to artifact corruption and high dimensionality of multi-lead electrocardiogram (ECG). In the present study, we proposed an automated single-beat MI detection and localization system using dual-Q tunable Q-factor wavelet transformation (Dual-Q TQWT) denoising algorithm. Methods After denoising and segmentation of ECG, a fourth-order wavelet tensor (leads × subbands × samples × beats) was constructed based on the discrete wavelet packet transform (DWPT), to represent the features considering the information of inter-beat, intra-beat, inter-frequency, and inter-lead. To red…
Dimension reduction: additional benefit of an optimal filter for independent component analysis to extract event-related potentials.
2011
The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the n…
Restoration and Enhancement of Historical Stereo Photos
2021
Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed, referred to as Stacked Median Restoration plus (SMR+). The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it …
Hilbert-Huang single-shot spatially multiplexed interferometric microscopy.
2018
Hilbert-Huang single-shot spatially multiplexed interferometric microscopy (H2S2MIM) is presented as the implementation of a robust, fast, and accurate single-shot phase estimation algorithm with an extremely simple, low-cost, and highly stable way to convert a bright field microscope into a holographic one using partially coherent illumination. Altogether, H2S2MIM adds high-speed (video frame rate) quantitative phase imaging capability to a commercially available nonholographic microscope with improved phase reconstruction (coherence noise reduction). The technique has been validated using a 20×/0.46 NA objective in a regular Olympus BX-60 upright microscope for static, as well as dynamic…
Impulse noise removal on an embedded, low memory SIMD processor
2003
Vector median filters efficiently reduce noise while preserving image details. However, their high computational complexity for color images makes them impractical for real-time systems. We propose new computationally efficient filtering algorithms, called index mapping filters (IMF). These filtering algorithms are accelerated by implementing them on a massively data parallel processor array. In addition to greater computational efficiency, these algorithms result in robust noise reduction of corrupted color images. Analyses of mean square error, signal-to-noise-ratio, and visual comparison metrics indicate that IMF are competitive with the vector median filter (VMF) in their ability to cor…
Multivariate denoising methods combining wavelets and principal component analysis for mass spectrometry data
2010
The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years, there has been a growing interest in using mass spectrometry for the detection of such biomarkers. The MS signal resulting from MALDI-TOF measurements is contaminated by different sources of technical variations that can be removed by a prior pre-processing step. In particular, denoising makes it possible to remove the random noise contained in the signal. Wavelet methodology associated with thresholding is usually used for this purpose. In this study, we adapted two multivariate denoising methods that combine wavelets and PCA to MS data. The objective was to o…
A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise
2014
Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.
Sound absorption prediction of linear damped acoustic resonators using a lightweight hybrid model
2019
International audience; A lightweight numerical method is developed to predict the sound absorption coefficient of resonators whose cross-section dimensions are significantly larger compared to the viscous and thermal boundary layer’s thicknesses. This method is based on the boundary layer theory and on the perturbations theory. According to the perturbations theory, in acoustical domains with large dimensions, the fluid viscosity and thermal conductivity only affect the boundary layers. The model proposed in this article combines the lossless Helmholtz wave equation derived from a perfect fluid hypothesis, with viscosity and thermal conductivity values of a real fluid to compute the sound …