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This paper proposes a new adaptation algorithm named Normalized Recursive Least Moduli (NRLM) algorithm which employs “p-modulus” of error and “q-norm” of filter input. p-modulus and q-norm are generalization of the modulus and norm used in complex-domain adaptive filters. The NRLM algorithm with p-modulus and q-norm makes adaptive filters fast convergent and robust against two types of impulse noise:...
This paper introduces a family of nonseparable multiscale decompositions for two-dimensional scattered data based on a sample grid dependent implementation of a Laplacian pyramid. This Laplacian pyramid for two-dimensional, irregular observations coincides with a slightly redundant lifting scheme for second generation wavelet decompositions. We can thus associate a frame of wavelet functions with...
Noise variation is an important parameter for many image denoising algorithms. This paper proposed a new two-step noise variation estimation algorithm based on image segmentation. In the first step, noisy image was smoothed and segmented by statistical region merge (SRM) algorithm. Then variation of every region was computed, and some regions were selected based on statistical rule to estimate the...
In this paper we consider active noise control (ANC) of impulsive noise having peaky distribution with heavy tail. Such impulsive noise can be modeled using non-Gaussian stable process for which second order moments do not exist. The most famous filtered-x least mean square (FxLMS) algorithm for ANC systems is based on second order moment of error signal, and hence, becomes unstable for the impulsive...
Image de-noising is an essential intermediate step in several medical applications related to brain MRI. The noise present in brain MRI degrades the performance of computer-aided analysis of these images. Therefore, the noise should be removed prior to subsequent processing. Non-local means (NLM) is a classical de-noising algorithm, which has been successfully applied for de-noising of brain MRI....
Speckle noise usually occurs in synthetic aperture radar (SAR) images , and SAR data is processed coherently. Speckle filters commonly are adaptive filters using local statistics such as mean and standard deviation, such as the Lee and its enhanced filters and median filter. They adapt the filter coefficients based on data within a fixed moving window, and this brings in contradiction between the...
Most existing distributed adaptive filtering algorithms focus on de- signing different information diffusion rules, regardless of the nature evolutionary characteristic of a distributed network. In this paper, we study the adaptive network from the game theoretic perspective and formulate the distributed adaptive filtering problem as a graphical evolutionary game. For the nodes in the network, the...
In this paper, we proposed an algorithm for estimating the density of salt & pepper noise in images with entropy inspection in wavelet domain. Based on the trait that energies of image signal and noise could be separated by wavelet transform, and on the fact that noise entropy in wavelet domain changes with approximate logarithm mode along with the noise level, we exhibit how the entropy values...
In this paper, we propose a golf video browsing system using three stage audio segmentation. To increase the accuracy of audio segment boundaries for golf video browsing on digital video recorder, the proposed three-stage audio segmentation algorithm consists of Gaussian Mixture Model (GMM)-based classification, GMM-Linear Discriminant Analysis (LDA)-based classification, and occupation ratio-based...
In order to remove the noise of sonar image more effectively, the adaptive over complete dictionary based on K-SVD algorithm is carried out in this paper. Given a set of training signals from noisy image, the predefined dictionary is trained so that the new dictionary leads to the best sparse representation for sonar image, but not for the noise. Experiments are provided to demonstrate the performance...
During acquisition of an image, from its source, noise becomes integral part of it, which is very difficult to remove. Various algorithms have been used in past to denoise images. Image denoising still has scope for improvement. In this paper we present a new image denoising algorithm based on combined effect of wavelet transform and median filtering. The algorithm removes most of the noisy part from...
At telecardiology, the ECG signals are transmitted and then followed by the information about the patients. Unfortunately sometimes due to the network congestion, some ECG signals maybe received to the wrong patient, therefore a fatal consequences maybe resulted. At this paper, we present a proposed watermarking technique to embed the information of patients on the ECG signals themselves. The proposed...
Edge information is the most vital high frequency information of an image, filtering an image to reduce noise while keeping the image details preserved is one of the most important issues. In this paper we proposed a method in which double median filtering stage is used to preserve edge details, which enhance the quality of image. The algorithm is carried out in two stages; first stage is detection...
To alleviate the tradeoff between the convergence rate and steady state error, an adaptive convex combination scheme-based adaptive FLANN filter is proposed for nonlinear ANC systems in this paper. The mixing parameter that controls the combination strategy is adapted to minimize the error of the overall filter by the gradient descent approach. Simulation results demonstrate that the proposed CFSLMS...
A block-based adaptive median filter, which aims to purify impulse noise from an MRI image, is discussed in the paper. The proposed filter blocks the image into several sub-images, and calculates the standard deviation of each sub-image. During filtering process, each point of the sub-image needs to be judged whether it is noise point or not, according to the average value of the filtering window...
To improve the tracking accuracy of an underwater maneuvering target, according to its characteristics of low speed and weak maneuvering performance, an adaptive Kalman filter is given based on the online estimation of the process noise variance. As the main filter analyzes the target motion, the process noise variance of the main filter is estimated by an auxiliary filter for being adaptively adjusted...
Normalized frequency domain LMS algorithm is attractive due to its low computational burden and fast convergence speed. However, it suffers from the deteriorated steady-state behavior in noncausal circumstances, which is always inevitable in many application scenarios. In this paper, the influence of several factors on the steady state behavior of the normalized frequency domain LMS algorithm is investigated...
In this paper, we present a new adaptive boundary filtering which is an improvement of the bilateral filtering algorithm. Bilateral filtering is an algorithm that is used for smoothing and preserving the edges in an image. This algorithm has proper capability when using with normal surface that have less number of regions. For texture area, many complicated regions are packed together e.g., hair and...
The article deals with the method for estimating the unfavorable living areas for people. The method is based on a distributed registration of the variations of the geomagnetic field and determining the area of their origin. The proposed algorithms are analyzed on the example of irregular geomagnetic pulsations of the Pi-2.
This paper presents a digital hybrid filter which can be applied to power electronics control systems. The filter suppresses high-frequency noises while still providing a fast step response, its weighting algorithm is based on an open-loop criteria that analyses the discrepancy between an Infinite Impulse Response (IIR) and a Moving Average (MA) filter. The filter performance is compared to classical...
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