Audio noise suppression based on neuromorphic saliency and phoneme adaptive filtering

2005 ◽  
Author(s):  
David V. Anderson Rongqiang Hu
Keyword(s):  
Adaptive Filtering ◽  
Noise Suppression

scholarly journals Robust Noise Suppression Technique for a LADAR System via Eigenvalue-Based Adaptive Filtering

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2311
Author(s):  
Xianzhao Xia ◽  
Rui Chen ◽  
Pinquan Wang ◽  
Yiqiang Zhao
Keyword(s):  
Adaptive Filtering ◽  
Noise Level ◽  
Noise Suppression ◽  
Simulation Analysis ◽  
Asymptotic Properties ◽  
Estimation Method ◽  
System Stability ◽  
Noise Level Estimation ◽  
Sample Covariance ◽  
Guided Filtering

The laser detection and ranging system (LADAR) is widely used in various fields that require 3D measurement, detection, and modeling. In order to improve the system stability and ranging accuracy, it is necessary to obtain the complete waveform of pulses that contain target information. Due to the inevitable noise, there are distinct deviations between the actual and expected waveforms, so noise suppression is essential. To achieve the best effect, the filters’ parameters that are usually set as empirical values should be adaptively adjusted according to the different noise levels. Therefore, we propose a novel noise suppression method for the LADAR system via eigenvalue-based adaptive filtering. Firstly, an efficient noise level estimation method is developed. The distributions of the eigenvalues of the sample covariance matrix are analyzed statistically after one-dimensional echo data are transformed into matrix format. Based on the boundedness and asymptotic properties of the noise eigenvalue spectrum, an estimation method for noise variances in high dimensional settings is proposed. Secondly, based on the estimated noise level, an adaptive guided filtering algorithm is designed within the gradient domain. The optimized parameters of the guided filtering are set according to an estimated noise level. Through simulation analysis and testing experiments on echo waves, it is proven that our algorithm can suppress the noise reliably and has advantages over the existing relevant methods.

FPGA-Based Re-Configurable Architecture for Window-Based Image Processing

2018 ◽  
pp. 273-310
Author(s):  
Kamarujjaman Sk ◽  
Manali Mukherjee ◽  
Mausumi Maitra
Keyword(s):  
Adaptive Filtering ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Digital Images ◽  
Median Filter ◽  
Hardware Architecture ◽  
Efficient Design ◽  
Filtering Method ◽  
Switching Median Filter ◽  
Noise Density

In this proposed book chapter, a simple but efficient presentation of Median Filter, Switching Median Filter, Adaptive Median Filter and Decision-Based Adaptive Filtering Method and their hardware architecture for FPGA is described for removal of up to 99% impulse noise from Digital Images. For hardware architecture, simulation is done using Xilinx ISE 14.5 software of XILINX. For implementation, these approaches utilize Genesys VIRTEX V FPGA device of XC5VLX50T device family. In this approach, we proposed an efficient design for suppression of impulse noise from digital images corrupted by up to 99% impulse noise using decision based adaptive filtering method as well as preserve the details of image. The method works in two different stages – noise detection using switching technique and finally noise suppression and restoration. Experimental results show that our method perform better in terms of PSNR below 80% noise density but above 80% noise density it is almost comparable with the latest methods.

FPGA-Based Re-Configurable Architecture for Window-Based Image Processing

2017 ◽  
pp. 1-46
Author(s):  
Kamarujjaman Sk ◽  
Manali Mukherjee ◽  
Mausumi Maitra
Keyword(s):  
Adaptive Filtering ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Digital Images ◽  
Median Filter ◽  
Hardware Architecture ◽  
Efficient Design ◽  
Filtering Method ◽  
Switching Median Filter ◽  
Noise Density

In this proposed book chapter, a simple but efficient presentation of Median Filter, Switching Median Filter, Adaptive Median Filter and Decision-Based Adaptive Filtering Method and their hardware architecture for FPGA is described for removal of up to 99% impulse noise from Digital Images. For hardware architecture, simulation is done using Xilinx ISE 14.5 software of XILINX. For implementation, these approaches utilize Genesys VIRTEX V FPGA device of XC5VLX50T device family. In this approach, we proposed an efficient design for suppression of impulse noise from digital images corrupted by up to 99% impulse noise using decision based adaptive filtering method as well as preserve the details of image. The method works in two different stages – noise detection using switching technique and finally noise suppression and restoration. Experimental results show that our method perform better in terms of PSNR below 80% noise density but above 80% noise density it is almost comparable with the latest methods.

Research on the White Noise Suppression by Adaptive Filtering of Genetic Algorithm

2012 ◽  
Vol 155-156 ◽  
pp. 989-994 ◽  
Author(s):  
Xiao Rong Tong
Keyword(s):  
Genetic Algorithm ◽  
White Noise ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Noise Suppression ◽  
Signal Transmission ◽  
Weight Vector ◽  
Mean Filter ◽  
The Mean ◽  
Simulation Results

Signal transmission is often subject to the disturbance of white noise. Owing to the spectrum of white noise can be found in the real number field, it is often difficult to filter out with the traditional filter. This article describes the methods of white noise suppression using adaptive filter and mean filter. First, using the genetic algorithm to optimize the weight vector of the adaptive filter, and then using the method of the mean filter to further filter, Simulation results show that the filter can effectively suppress white noise.

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