Search results for "denoising"
showing 10 items of 32 documents
A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault
2020
This paper proposes a smart sensing method for real-time monitoring of low voltage series arc fault. It is based on the wavelet coefficient mean-difference algorithm and the four spikes appearing within two fundamental periods criterion with adaptive threshold. The method also uses the hard thresholding wavelet denoising with the universal threshold. An arc fault factor and a load adaptation factor are introduced and combined with a correction factor, so allowing the selection of the adaptive threshold in real-time and the series arc fault detection.
Strengthened splitting methods for computing resolvents
2021
In this work, we develop a systematic framework for computing the resolvent of the sum of two or more monotone operators which only activates each operator in the sum individually. The key tool in the development of this framework is the notion of the “strengthening” of a set-valued operator, which can be viewed as a type of regularisation that preserves computational tractability. After deriving a number of iterative schemes through this framework, we demonstrate their application to best approximation problems, image denoising and elliptic PDEs. FJAA and RC were partially supported by the Ministry of Science, Innovation and Universities of Spain and the European Regional Development Fund …
Wavelet Analysis and Denoising: New Tools for Economists
2007
This paper surveys the techniques of wavelets analysis and the associated methods of denoising. The Discrete Wavelet Transform and its undecimated version, the Maximum Overlapping Discrete Wavelet Transform, are described. The methods of wavelets analysis can be used show how the frequency content of the data varies with time. This allow us to pinpoint in time such events as major structural breaks. The sparse nature of the wavelets representation also facilitates the process of noise reduction by nonlinear \textit{wavelet shrinkage,} which can be used to reveal the underlying trends in economic data. An application of these techniques to the UK real GDP (1873--2001) is described. The purpo…
The impact of noise estimation on dehazing
2020
International audience; Under haze or fog, the quality of the images is degraded due to the atmosphere, causing the details of the images to be difficult to identify by observers and computer vision systems. Such images contain noise, which is mainly due either to environment (extrinsic noise) or sensor (intrinsic noise). As the transmission of light coming from the scenes' objects is exponentially attenuated and comes quickly down to zero in presence of haze, the noise is greatly amplified at high haze densities and long distances. In order to investigate the importance of the accurate estimation and the removal of noise from hazy images, we used the CHIC (Color Hazy Image for Comparison) …
On GPU-accelerated fast direct solvers and their applications in image denoising
2015
Temporal Denoising of Kinect Depth Data
2012
The release of the Microsoft Kinect has attracted the attention of researchers in a variety of computer science domains. Even though this device is still relatively new, its recent applications have shown some promising results in terms of replacing current conventional methods like the stereo-camera for robotics navigation, multi-camera system for motion detection and laser scanner for 3D reconstruction. While most work around the Kinect is on how to take full advantage of its capabilities, so far only a few studies have been carried out on the limitations of this device and fewer that provide solutions to enhance the precision of its measurements. In this paper, we review and analyse curr…
Modified total variation regularization using fuzzy complement for image denoising
2015
In this paper, we propose a denoising algorithm based on the Total Variation (TV) model. Specifically, we associate to the regularization term of the Rodin-Osher-Fatimi (ROF) functional a small weight whenever denoising is performed in edge and texture regions, which means less regularization and more details preservation. On the other hand, a large weight is associated if the region being filtered is smooth which means noise will be well suppressed. The weight computation is inspired from the fuzzy edge complement. Experiments on well-known images and comparison with state of the art denoising algorithms demonstrate that the proposed method not only presents good denoising performance but …
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 …
Processo di denoising per l'acquisizione di segnali di scariche parziali mediante trasformata wavelet discreta (DWT)
2009
Analysis of microtomographic images of porous heterogeneous materials
2015
In this work, we study the phases of image processing chain of microtomographic imag- ing in order to obtain reliable results while optimizing the time spent on denoising and segmentation. We consider that the decisions made at the early phases of the processing chain are most important and the selection made there essentially determine the overall quality of imaging process. We also compare here various denoising method qualita- tively, however, we think that the pure noise removal ability is not the only requirement for noise removal in microtomographic images. By proper denoising we can affect selec- tion of segmentation methods and, thus, also the quality of the analysis. Additionally, …