Search results for "noise reduction"
showing 10 items of 71 documents
Restoration of Vertical Line Scratches with a Distributed Genetic Algorithm
2006
This contribution approaches the problem of scratch restoration in old movies as a optimisation's problem. The functional based on the statistical properties of the image around the scratch is optimised using an ad-hoc genetic algorithm. Given the large amount of the computational time needed by genetic algorithms, a network of standard workstations with heterogeneous operating systems has been used. Each workstation in the network works on each scratch to perform the restoration, and a specific machine works as root node with the task of distributing jobs on the network and adding the outputted restored scratches back into the image.
A combined CWT-DWT method using model-based design simulator for partial discharges online detection
2009
The suppression of noises is fundamental in onsite Partial Discharge (PD) measurements. For this purpose, the wavelet transform analysis method has been developed and it is a powerful tool for processing the transient and suddenly changing signals. As the wavelet transform possesses the properties of multi-scale analysis and time-frequency domain localization, it is also particularly suitable to process the suddenly changing signals of the partial discharge pulse (PD). In this paper, an improved Wavelet denoising method developed by a model-based design software is presented. Simulations are provided as well as some results obtained during laboratory experiment and on-line PD measurements. …
Adaptive-threshold neural spike detection by noise-envelope tracking
2007
A new method for adaptive threshold setting is implemented and used in two threshold-based spike detectors: simple threshold and nonlinear energy operator. Detection quality assessment is performed using both a set of artificially generated signals and a real neural recording. Receiver operating curves are obtained and results show that, compared to fix threshold, adaptive threshold setting yields performance improvement.
On 1-Laplacian Elliptic Equations Modeling Magnetic Resonance Image Rician Denoising
2015
Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called $1$-Laplacian operator and special care is needed to properly formulate the problem. The rician statistics of the data are introduced through a singular equation with a reaction term defined in terms of modified first order Bessel functions. An existence theory is provided here together with other qualitative properties of the solutions. Remarkably, each positive global minimum of the associated functional is one of such solutions. Moreover, we directly …
Resuming Shapes with Applications
2004
Many image processing tasks need some kind of average of different shapes. Frequently, different shapes obtained from several images have to be summarized. If these shapes can be considered as different realizations of a given random compact set, then the natural summaries are the different mean sets proposed in the literature. In this paper, new mean sets are defined by using the basic transformations of Mathematical Morphology (dilation, erosion, opening and closing). These new definitions can be considered, under some additional assumptions, as particular cases of the distance average of Baddeley and Molchanov. The use of the former and new mean sets as summary descriptors of shapes is i…
Multiresolution Analysis for Meshes with Appearance Attributes
2005
International audience; We present a new multiresolution analysis framework for irregular meshes with attributes based on the lifting scheme. We introduce a surface prediction operator to compute the detail coefficients for the geometry and the attributes of the model. Attribute analysis gives appearance information to complete the geometrical analysis of the model. A set of experimental results are given to show the efficiency of our framework. We present two applications to adaptive visual-ization and denoising.
Multiresolution Analysis for Irregular Meshes
2003
International audience; The concept of multiresolution analysis applied to irregular meshes has become more and more important. Previous contributions proposed a variety of methods using simplification and/or subdivision algorithms to build a mesh pyramid. In this paper, we propose a multiresolution analysis framework for irregular meshes with attributes. Our framework is based on simplification and subdivision algorithms to build a mesh pyramid. We introduce a surface relaxation operator that allows to build a non-uniform subdivision for a low computational cost. Furthermore, we generalize the relaxationoperator to attributes such as color, texture, temperature, etc. The attribute analysis…
ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces
2009
Abstract In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The inter…
Scene-based noise reduction on a smart camera
2012
International audience; Raw output data from CMOS image sensors tends to exhibit significant noise called Fixed-Pattern Noise (FPN) due to on-die variations between pixel photodetectors. FPN is often corrected by subtracting its value, estimated through calibration, from the sensor's raw signal. This paper introduces an on-line scene-based technique for an improved FPN compensation which does not rely on calibration, and hence is more robust to the dynamic changes in the FPN which may occur slowly over time. Development has been done with a special emphasis on real-time hardware implementation on a FPGA-based smart camera. Experimental results on different scenes are depicted showing that t…
Noise removal using a nonlinear two-dimensional diffusion network
1998
Un reseau electrique non lineaire bidimensionnel, constitue de N×N cellules identiques, et modelisant l’equation de Nagumo discrete est presente. A l’aide d’une nouvelle description de la fonction non lineaire, on peut predire analytiquement l’evolution temporelle de la partie coherente du signal, ainsi que celle des perturbations de petites amplitudes qui lui sont superposees. Enfin, des applications a l’amelioration du rapport signal sur bruit, ou au traitement d’images sont suggerees.