Noise reduction

About: Noise reduction is a research topic. Over the lifetime, 25121 publications have been published within this topic receiving 300815 citations. The topic is also known as: denoising & noise removal.

Time-Domain Signal Analysis Using Adaptive Notch Filter

Abstract: Noise reduction and signal decomposition are among important and practical issues in time-domain signal analysis. This paper presents an adaptive notch filter (ANF) to achieve both these objectives. For noise reduction purpose, the proposed adaptive filter successfully extracts a single sinusoid of a possibly time-varying nature from a noise-corrupted signal. The paper proceeds with introducing a chain of filters which is capable of estimating the fundamental frequency of a signal composed of harmonically related sinusoids, and of decomposing it into its constituent components. The order of differential equations governing this algorithm is 2n+1, where n is the number of constituent sinusoids that should be extracted. Stability analysis of the proposed algorithm is carried out based on the application of the local averaging theory under the assumption of slow adaptation. When compared with the conventional Fourier analysis, the proposed method provides instantaneous values of the constituting components. Moreover, it is adaptive with respect to the fundamental frequency of the signal. Simulation results verify the validity of the presented algorithm and confirm its desirable transient and steady-state performances as well as its desirable noise characteristics

The Noise Clinic: a Blind Image Denoising Algorithm

Abstract: This paper describes the complete implementation of a blind image denoising algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD) noise model. In a second step, the image is denoised by a multiscale adaptation of the Non-local Bayes denoising method. We focus here on a careful analysis of the denoising step and present a detailed discussion of the influence of its parameters. Extensive commented tests of the blind denoising algorithm are presented, on real JPEG images and on scans of old photographs. Source Code The source code (ANSI C), its documentation, and the online demo are accessible at the IPOL web page of this article1.

Image Reconstruction and Noise Evaluation in Photon Time-of-Flight Assisted Positron Emission Tomography

Abstract: In positron CT, the path difference of annhilation pair gamma rays can be measured by time-of-flight (TOF) difference of pair gamma rays. This TOF information gives us rough position information along a projection line and will reduce noise propagation in the reconstruction process. A reconstruction algorithm for TOF-positron computed tomography (PCT) based on the back-projection with 1-dimensional weight and 2-dimensional filtering is presented. Also a formula to evaluate the variance of the reconstructed image and the optimal back-projection function are presented. The advantage of TOF-PCT over conventional PCT was investigated in view of noise figure. An example of such noise figure evaluations for CsF and liquid Xenon scintillators is given.

Superresolution and noise filtering using moving least squares

Abstract: An irregularly spaced sampling raster formed from a sequence of low-resolution frames is the input to an image sequence superresolution algorithm whose output is the set of image intensity values at the desired high-resolution image grid. The method of moving least squares (MLS) in polynomial space has proved to be useful in filtering the noise and approximating scattered data by minimizing a weighted mean-square error norm, but introducing blur in the process. Starting with the continuous version of the MLS, an explicit expression for the filter bandwidth is obtained as a function of the polynomial order of approximation and the standard deviation (scale) of the Gaussian weight function. A discrete implementation of the MLS is performed on images and the effect of choice of the two dependent parameters, scale and order, on noise filtering and reduction of blur introduced during the MLS process is studied

Common Mode Noise Reduction for Boost Converters Using General Balance Technique

Abstract: In this paper, the boost converter model for electromagnetic interference noise analysis is first investigated. Based on this model, a general balance concept is proposed to cancel the common mode noise. Theoretical analysis, simulation, and experiment prove that the proposed balance technique is efficient enough to reduce common mode noise.