Projection and interpolation based techniques for structured and impulsive noise filtering

In this chapter we present the relevant mathematical background to address two well defined signal and image processing problems. Namely, the problem of structured noise filtering and the problem of interpolation of missing data. The former is addressed by recourse to oblique projection based techniques whilst the latter, which can be considered equivalent to impulsive noise filtering, is tackled by appropriate interpolation methods.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

Mathematical analysis for perceived annoyance of impulsive sounds in terms of physical factors

From the customer satisfaction point of view, sound quality of any product has become one of the important factors these days. The primary objective of this research is to determine factors which affect the acceptability of impulse noise. Though the analysis is based on a sample impulse sound file of a Commercial printer, the results can be applied to other similar impulsive noise. It is assumed that impulsive noise can be tuned to meet the accepTable criteria. Thus it is necessary to find the most significant factors which can be controlled physically. This analysis is based on a single impulse. A sample impulsive sound file is tweaked for different amplitudes, background noise, attack time, release time and the spectral content. A two level factorial design of experiments (DOE) is applied to study the significant effects and interactions. For each impulse file modified as per the DOE, the magnitude of perceived annoyance is calculated from the objective metric developed recently at Michigan Technological University. This metric is based on psychoacoustic criteria such as loudness, sharpness, roughness and loudness based impulsiveness. Software called ‘Artemis V11.2’ developed by HEAD Acoustics is used to calculate these psychoacoustic terms. As a result of two level factorial analyses, a new objective model of perceived annoyance is developed in terms of above mentioned physical parameters such as amplitudes, background noise, impulse attack time, impulse release time and the spectral content. Also the effects of the significant individual factors as well as two level interactions are also studied. The results show that all the mentioned five factors affect annoyance level of an impulsive sound significantly. Thus annoyance level can be reduced under the criteria by optimizing the levels. Also, an additional analysis is done to study the effect of these five significant parameters on the individual psychoacoustic metrics.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

Detection of signals corrupted by the combination of Gaussian and Non-Gaussian noise

The detection of signals in the presence of noise is one of the most basic and important problems encountered by communication engineers. Although the literature abounds with analyses of communications in Gaussian noise, relatively little work has appeared dealing with communications in non-Gaussian noise. In this thesis several digital communication systems disturbed by non-Gaussian noise are analysed. The thesis is divided into two main parts. In the first part, a filtered-Poisson impulse noise model is utilized to calulate error probability characteristics of a linear receiver operating in additive impulsive noise. Firstly the effect that non-Gaussian interference has on the performance of a receiver that has been optimized for Gaussian noise is determined. The factors affecting the choice of modulation scheme so as to minimize the deterimental effects of non-Gaussian noise are then discussed. In the second part, a new theoretical model of impulsive noise that fits well with the observed statistics of noise in radio channels below 100 MHz has been developed. This empirical noise model is applied to the detection of known signals in the presence of noise to determine the optimal receiver structure. The performance of such a detector has been assessed and is found to depend on the signal shape, the time-bandwidth product, as well as the signal-to-noise ratio. The optimal signal to minimize the probability of error of; the detector is determined. Attention is then turned to the problem of threshold detection. Detector structure, large sample performance and robustness against errors in the detector parameters are examined. Finally, estimators of such parameters as. the occurrence of an impulse and the parameters in an empirical noise model are developed for the case of an adaptive system with slowly varying conditions.

High Quality Acoustic Time History Measurements of Rotor Harmonic Noise in Confined Spaces

A methodology has been developed and presented to enable the use of small to medium scale acoustic hover facilities for the quantitative measurement of rotor impulsive noise. The methodology was applied to the University of Maryland Acoustic Chamber resulting in accurate measurements of High Speed Impulsive (HSI) noise for rotors running at tip Mach numbers between 0.65 and 0.85 – with accuracy increasing as the tip Mach number was increased. Several factors contributed to the success of this methodology including: • High Speed Impulsive (HSI) noise is characterized by very distinct pulses radiated from the rotor. The pulses radiate high frequency energy – but the energy is contained in short duration time pulses. • The first reflections from these pulses can be tracked (using ray theory) and, through adjustment of the microphone position and suitably applied acoustic treatment at the reflected surface, reduced to small levels. A computer code was developed that automates this process. The code also tracks first bounce reflection timing, making it possible to position the first bounce reflections outside of a measurement window. • Using a rotor with a small number of blades (preferably one) reduces the number of interfering first bounce reflections and generally improves the measured signal fidelity. The methodology will help the gathering of quantitative hovering rotor noise data in less than optimal acoustic facilities and thus enable basic rotorcraft research and rotor blade acoustic design.

Kohinan poisto spektrikuvista pehmeillä morfologisilla suodattimilla

Tämän diplomityön tavoitteena oli tutkia kohinan poistoa spektrikuvista käyttäen pehmeitä morfologisia suodattimia. Työssä painotettiin impulssimaisen kohinan suodattamista. Suodattimien toimintaa arvioitiin numeerisesti keskimääräisen itseisarvovirheen, neliövirheen sekä signaali-kohinasuhteen avulla ja visuaalisesti tarkastelemalla suodatettuja kuvia sekä niiden yksittäisiä spektritasoja. Käytettyjä suodatusmenetelmiä olivat suodatus kuvapisteittäin spektrin suunnassa, suodatus koko spektrissä sekä kuutiomenetelmä ja komponenteittainen suodatus. Suodatettavat kuvat sisälsivät joko suola ja pippuri- tai bittivirhekohinaa. Parhaimmat suodatustulokset sekä numeeristen virhekriteerien että visuaalisen tarkastelun perusteella saatiin komponenteittaisella sekä kuvapisteittäisellä menetelmällä. Työssä käytetyt menetelmät on esitetty algoritmimuodossa. Suodatinalgoritmien toteutukset ja suodatuskokeet tehtiin Matlab-ohjelmistolla.

Eliminação de ruído impulsivo em imagens coloridas usando um filtro mediano seletivo e retoque digital

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Implementação em software da codificação de canal em ADSL: um estudo de caso sobre os efeitos do ruído impulsivo na transmissão de vídeo

Este trabalho apresenta a implementação em software da codificação de canal utilizada no padrão ADSL. A teoria da codificação de canal e descrita, bem como a codificação de canal implementada no Software Modem ADSL utilizando o ambiente de desenvolvimento Ptolemy II. A implementação de um modelo de ruído impulsivo também é apresentada. Para garantir que a implementação obedeça o padrão do ADSL, testes utilizando o analisador de sistemas DSL TraceSpan são descritos. O trabalho apresenta ainda um exemplo de aplicação do Software Modem ADSL, caracterizado por um estudo de caso sobre os efeitos do ruído impulsivo na transmissão de vídeo, analisando o impacto de alguns parâmetros da codificação de canal na correção dos erros.

Medidas para caracterização de crosstalk e ruído impulsivo em sistemas DSL

O presente trabalho apresenta testes e experimentos laboratoriais para medição de crosstalk e ruído impulsivo em sistemas DSL, os quais são de grande importância para o aperfeiçoamento e evolução deste tipo de tecnologia. O estudo do crosstalk voltou-se a uma campanha de medições em cabos telefônicos reais de curto comprimento e operando em altas frequências. Os resultados destas medidas foram utilizados no cálculo da capacidade de transmissão de sistemas DSL operando neste cenário ainda pouco explorado. O estudo do ruído impulsivo foi focado no desenvolvimento de um sistema digitalizador de sinais de linha telefônica possibilitando a medição real deste tipo de fenômeno.

Sistema de seguridad basado en la clasificación de eventos sonoros

La teoría de reconocimiento y clasificación de patrones y el aprendizaje automático son actualmente áreas de conocimiento en constante desarrollo y con aplicaciones prácticas en múltiples ámbitos de la industria. El propósito de este Proyecto de Fin de Grado es el estudio de las mismas así como la implementación de un sistema software que dé solución a un problema de clasificación de ruido impulsivo, concretamente mediante el desarrollo de un sistema de seguridad basado en la clasificación de eventos sonoros en tiempo real. La solución será integral, comprendiendo todas las fases del proceso, desde la captación de sonido hasta el etiquetado de los eventos registrados, pasando por el procesado digital de señal y la extracción de características. Para su desarrollo se han diferenciado dos partes fundamentales; una primera que comprende la interfaz de usuario y el procesado de la señal de audio donde se desarrollan las labores de monitorización y detección de ruido impulsivo y otra segunda centrada únicamente en la clasificación de los eventos sonoros detectados, definiendo una arquitectura de doble clasificador donde se determina si los eventos detectados son falsas alarmas o amenazas, etiquetándolos como de un tipo concreto en este segundo caso. Los resultados han sido satisfactorios, mostrando una fiabilidad global en el proceso de entorno al 90% a pesar de algunas limitaciones a la hora de construir la base de datos de archivos de audio, lo que prueba que un dispositivo de seguridad basado en el análisis de ruido ambiente podría incluirse en un sistema integral de alarma doméstico aumentando la protección del hogar. ABSTRACT. Pattern classification and machine learning are currently expertise areas under continuous development and also with extensive applications in many business sectors. The aim of this Final Degree Project is to study them as well as the implementation of software to carry on impulsive noise classification tasks, particularly through the development of a security system based on sound events classification. The solution will go over all process stages, from capturing sound to the labelling of the events recorded, without forgetting digital signal processing and feature extraction, everything in real time. In the development of the Project a distinction has been made between two main parts. The first one comprises the user’s interface and the audio signal processing module, where monitoring and impulsive noise detection tasks take place. The second one is focussed in sound events classification tasks, defining a double classifier architecture where it is determined whether detected events are false alarms or threats, labelling them from a concrete category in the latter case. The obtained results have been satisfactory, with an overall reliability of 90% despite some limitations when building the audio files database. This proves that a safety device based on the analysis of environmental noise could be included in a full alarm system increasing home protection standards.

OTHR impulsive interference suppression in strong clutter background

External interferences can severely degrade the performance of an Over-the-horizon radar (OTHR), so suppression of external interferences in strong clutter environment is the prerequisite for the target detection. The traditional suppression solutions usually began with clutter suppression in either time or frequency domain, followed by the interference detection and suppression. Based on this traditional solution, this paper proposes a method characterized by joint clutter suppression and interference detection: by analyzing eigenvalues in a short-time moving window centered at different time position, Clutter is suppressed by discarding the maximum three eigenvalues at every time position and meanwhile detection is achieved by analyzing the remained eigenvalues at different position. Then, restoration is achieved by forward-backward linear prediction using interference-free data surrounding the interference position. In the numeric computation, the eigenvalue decomposition (EVD) is replaced by values decomposition (SVD) based on the equivalence of these two processing. Data processing and experimental results show its efficiency of noise floor falling down about 10-20 dB.

Fourier´s law from a chain of coupled anharmonic oscillators under energy conserving shot noise.

We analyze the transport of heat along a chain of particles interacting through anharmonic potentials consisting of quartic terms in addition to harmonic quadratic terms and subject to heat reservoirs at its ends. Each particle is also subject to an impulsive shot noise with exponentially distributed waiting times whose effect is to change the sign of its velocity, thus conserving the energy of the chain. We show that the introduction of this energy conserving stochastic noise leads to Fourier's law. That is for large system size L the heat current J behaves as J ‘approximately’ 1/L, which amounts to say that the conductivity k is constant. The conductivity is related to the current by J = kΔT/L, where ΔT is the difference in the temperatures of the reservoirs. The behavior of heat conductivity k for small intensities¸ of the shot noise and large system sizes L are obtained by assuming a scaling behavior of the type k = ‘L POT a Psi’(L’lambda POT a/b’) where a and b are scaling exponents. For the pure harmonic case a = b = 1, characterizing a ballistic conduction of heat when the shot noise is absent. For the anharmonic case we found values for the exponents a and b smaller then 1 and thus consistent with a superdiffusive conduction of heat without the shot noise. We also show that the heat conductivity is not constant but is an increasing function of temperature.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.