scholarly journals A Study on Distortion Estimation Based on Image Gradients

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 639
Author(s):  
Sin Chee Chin ◽  
Chee-Onn Chow ◽  
Jeevan Kanesan ◽  
Joon Huang Chuah
Keyword(s):  
Multiplicative Noise ◽  
Additive Noise ◽  
Image Quality Assessment ◽  
Impulsive Noise ◽  
Image Noise ◽  
Noise Parameters ◽  
Estimation Algorithms ◽  
Feature Extractor ◽  
Noise Data ◽  
Image Gradients

Image noise is a variation of uneven pixel values that occurs randomly. A good estimation of image noise parameters is crucial in image noise modeling, image denoising, and image quality assessment. To the best of our knowledge, there is no single estimator that can predict all noise parameters for multiple noise types. The first contribution of our research was to design a noise data feature extractor that can effectively extract noise information from the image pair. The second contribution of our work leveraged other noise parameter estimation algorithms that can only predict one type of noise. Our proposed method, DE-G, can estimate additive noise, multiplicative noise, and impulsive noise from single-source images accurately. We also show the capability of the proposed method in estimating multiple corruptions.

scholarly journals GPS Signal Detection under Multiplicative and Additive Noise

2012 ◽  
Vol 66 (4) ◽  
pp. 479-500 ◽  
Author(s):  
P. Huang ◽  
Y. Pi ◽  
I. Progri
Keyword(s):  
Signal Detection ◽  
Urban Areas ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Power Level ◽  
Signal Propagation ◽  
Signal Acquisition ◽  
Detection Scheme ◽  
Additive And Multiplicative Noise ◽  
Gps Signal Acquisition

In some Global Positioning System (GPS) signal propagation environments, especially in the ionosphere and urban areas with heavy multipath, GPS signal encounters not only additive noise but also multiplicative noise. In this paper we compare and contrast the conventional GPS signal acquisition method which focuses on handling GPS signal acquisition with additive noise, with the enhanced GPS signal processing under multiplicative noise by proposing an extension of the GPS detection mechanism, to include the GPS detection model that explains detection of the GPS signal under additive and multiplicative noise. For this purpose, a novel GPS signal detection scheme based on high order cyclostationarity is proposed. The principle is introduced, the GPS signal detection structure is described, the ambiguity of initial PseudoRandom Noise (PRN) code phase and Doppler shift of GPS signal is analysed. From the simulation results, the received GPS signal at low power level, which is degraded by additive and multiplicative noise, can be detected under the condition that the received block of GPS data length is at least 1·6 ms and sampling frequency is at least 5 MHz.

Nonequilibrium Phenomena in Globally Coupled Phase Oscillators: Noise-Induced Bifurcations, Clustering, and Switching

1997 ◽  
Vol 07 (04) ◽  
pp. 917-922
Author(s):  
Seon Hee Park ◽  
Seunghwan Kim ◽  
Seung Kee Han
Keyword(s):  
Phase Transition ◽  
Noise Intensity ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Critical Value ◽  
Phase Oscillators ◽  
Deterministic Systems ◽  
Nonequilibrium Phenomena ◽  
Noise Models ◽  
Coupled Phase Oscillators

The Nonequilibrium phenomena in a class of globally coupled phase oscillators systems with multiplicative noise are studied. It is shown that at the critical value of the noise intensity the systems undergo a phase transition and converge to clustered states. We also show that the time delay in the interaction between oscillators gives rise to the switching phenomena of clusters. These phenomena are noise-induced effects which cannot be seen in the deterministic systems or in the simple additive noise models.

scholarly journals Three-dimensional personnel safety positioning based on improved UKF under complex coal mine environment

2021 ◽  
Vol 303 ◽  
pp. 01054
Author(s):  
Hongxiang Xu ◽  
Xingzhen Bai ◽  
Lujie Zhou ◽  
Peng Liu
Keyword(s):  
Multiplicative Noise ◽  
Additive Noise ◽  
Coal Mines ◽  
Cluster Head ◽  
Three Dimensional ◽  
Practical Significance ◽  
Mine Environment ◽  
Personnel Safety ◽  
And Performance ◽  
Positioning Algorithm

Aiming at the problems of strong interference and poor positioning accuracy in coal mines, this paper proposes a positioning algorithm for accurate detection of personnel safety. It is of great practical significance to detect the safety movement track of underground personnel. In this paper, WSNs distributed in coal mines are divided into several clusters by clustering method. Each cluster has a certain number of sensors, which can communicate with each other to keep the estimation consistency, and send the collected data to the cluster head (CH) node. System noise includes additive noise and multiplicative noise. In order to improve the accuracy of estimation, an improved UKF algorithm is proposed. The simulation results show that the improved UKF algorithm improves the accuracy and performance of estimation, and allows better location of the underground personnel.

A Novel Illumination Compensation Method Using Wavelet Packet Transformation

2011 ◽  
Vol 317-319 ◽  
pp. 897-900
Author(s):  
Zhen Hua Zhao ◽  
Xiao Hong Hao
Keyword(s):  
Multiplicative Noise ◽  
Additive Noise ◽  
Recognition Performance ◽  
Wavelet Packet ◽  
Recognition Rate ◽  
Face Image ◽  
Experimental Results ◽  
Illumination Compensation ◽  
Wavelet Packet Transformation ◽  
Facial Images

A novel illumination compensate method is proposed in this paper to improve recognition performance. A modified lighting model called Lambertin which includes additive noise and multiplicative noise are presented firstly. Then, additive noise is removed by using wavelet packet transformation. Next, the processed image is transformed into logarithm domain and the multiplicative noise, which has been named additive noise, is removed by means of the same above algorithm. Finally, a compensated face image is obtained. We examine the proposed method on Yale extended B database compared with other methods. Experimental results show that our algorithm improves by 3%~12% recognition rate. It can effectively adjust the facial images for varying illumination conditions and also improve the recognition performance and robustness.

Impact of Time Delay and Cross-Correlated Gaussian Colored Noises on Dynamical Characteristics and Stochastic Resonance for a Metapopulation System

2020 ◽  
pp. 2150024
Author(s):  
Kang-Kang Wang ◽  
De-Cai Zong ◽  
Ya-Jun Wang ◽  
Sheng-Hong Li
Keyword(s):  
Time Delay ◽  
Stochastic Resonance ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Resonant Peak ◽  
Noise Correlation ◽  
Ecological Stability ◽  
Correlation Times ◽  
Correlation Strength

In this paper, the regime shift behaviors between the prosperous state and the extinction state and stochastic resonance (SR) phenomenon for a metapopulation system subjected to time delay and correlated Gaussian colored noises are investigated. Through the numerical calculation of the modified potential function and the stationary probability density function (SPDF), one can make clearly the following results: Both multiplicative noise and noise correlation times can improve effectively the ecological stability and prolong the survival time of the system; while additive noise, time delay and noise correlation strength can weaken significantly the biological stability and speed up the extinction of the population. As for the signal-to-noise ratio (SNR), it is found that time delay, multiplicative noise and noise correlation strength can all impair the SR effect. Conversely, the two noise correlation times and additive noise are in favor of the improvement of the peak values of SNR. It is particularly worth mentioning that in the case of [Formula: see text], time delay [Formula: see text] and self-correlation time [Formula: see text] of the additive noise display exactly the opposite effect on the stimulation of the resonant peak in the SNR–[Formula: see text] plots.

Stochastic Resonance in FitzHugh-Nagumo Neural Model

2013 ◽  
Vol 415 ◽  
pp. 298-302
Author(s):  
Deng Rong Zhou ◽  
Jian Chun Gong ◽  
Dan Li
Keyword(s):  
Stochastic Resonance ◽  
Adiabatic Approximation ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Signal To Noise Ratio ◽  
Neural Model ◽  
System Parameters ◽  
Maximum Value ◽  
External Incentives ◽  
Delayed Time

Stochastic resonance is a non-linear phenomenon where the output response of the dynamic system reaches the maximum value under the joint action of a certain intensity of noises and external incentives. In this paper, the phenomenon of stochastic resonance in a FitzHugh-Nagumo neural (FHN) model is studied. For the case that the frequency of the HF signal is much higher than that of the LF signal, under the adiabatic approximation condition, the expression of the signal-to-noise ratio (SNR) with respect to the LF signal is obtained. It is shown that, the SNR is a non-monotonous function of the amplitude and frequency of the HF signal. In addition, the SNR varies non-monotonically with increasing the intensities of the multiplicative and additive noise, with increasing the delayed-time as well as increasing the system parameters of the FHN model. The influence of the correlation time of the colored multiplicative noise and the influence of the coupling strength between the multiplicative and additive noise on the SNR is discussed.

scholarly journals A Multiplicative Noise Removal Approach Based on Partial Differential Equation Model

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Bo Chen ◽  
Jin-Lin Cai ◽  
Wen-Sheng Chen ◽  
Yan Li
Keyword(s):  
Fourth Order ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Speckle Noise ◽  
Noise Removal ◽  
Equation Model ◽  
Superior Performance ◽  
Pde Model ◽  
Novel Approach ◽  
Fourth Order Pde

Multiplicative noise, also known as speckle noise, is signal dependent and difficult to remove. Based on a fourth-order PDE model, this paper proposes a novel approach to remove the multiplicative noise on images. In practice, Fourier transform and logarithm strategy are utilized on the noisy image to convert the convolutional noise into additive noise, so that the noise can be removed by using the traditional additive noise removal algorithm in frequency domain. For noise removal, a new fourth-order PDE model is developed, which avoids the blocky effects produced by second-order PDE model and attains better edge-preserve ability. The performance of the proposed method has been evaluated on the images with both additive and multiplicative noise. Compared with some traditional methods, experimental results show that the proposed method obtains superior performance on different PSNR values and visual quality.

STOCHASTIC RESONANCE IN A TIME-DELAYED BISTABLE SYSTEM WITH COLORED COUPLING BETWEEN NOISE TERMS

2012 ◽  
Vol 26 (30) ◽  
pp. 1250149 ◽  
Author(s):  
XIAOQIN LUO ◽  
DAN WU ◽  
SHIQUN ZHU
Keyword(s):  
Time Delay ◽  
Stochastic Resonance ◽  
Coupling Strength ◽  
Multiplicative Noise ◽  
Additive Noise ◽  
Bistable System ◽  
Initial Condition

The phenomenon of stochastic resonance (SR) in a time-delayed bistable system with colored coupling between multiplicative and additive noise terms is investigated. The SR can be induced by the multiplicative noise, the time delay and the coupling strength between noise terms. Meanwhile, the SR is affected by the initial condition of the system.

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