Adaptive algorithm for impulse noise suppression from still images and its real time implementation

2011 ◽  
Author(s):  
S. Zoican
Keyword(s):  
Real Time ◽  
Adaptive Algorithm ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Still Images

scholarly journals Execution of Median Filter Built on FPGA for Trimming Noise Meeting the Real Time Requirements

2019 ◽  
Vol 8 (4) ◽  
pp. 7855-7858
Keyword(s):  
Real Time ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Median Filter ◽  
Sliding Window ◽  
Spatial Filter ◽  
Effective Technique ◽  
The Real ◽  
Time Requirements ◽  
Suppression Process

As images plays a vital in all aspects, there is a need to met the real time requirements in processing the image. Major challenges raised in processing the image is noise. The utmost typical difficult is effective denoising creation as well as quick functioning in the processing of digital image noise suppression process for the need of real time consequences to afford image with high quality this project was introduced. Generally filters plays a major role to remove the impulse noise in acquired images. The filter named sliding window spatial filter which is familiar as median filter is effective technique to eradicate impulse noise from the devoleped image. But in real time, it is very difficult to execute. To overcome this, FPGA methodology is introduced to fulfills the support besides the optimization of major constraints like area, speed, power. In addition to this, it assures technical sustenance of eradicating noise in image as per requirements in real time. Regarding the design and structure appearances in FPGA, Xilinx software is used for simulation and code has been written in Verilog language.

scholarly journals Real-Time Impulse Noise Suppression from Images Using an Efficient Weighted-Average Filtering

2015 ◽  
Vol 22 (8) ◽  
pp. 1050-1054 ◽  
Author(s):  
Hossein Hosseini ◽  
Farzad Hessar ◽  
Farokh Marvasti
Keyword(s):  
Real Time ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Weighted Average

The Design of a Wavelet-Based Neural Network Adaptive Filter

2013 ◽  
Vol 860-863 ◽  
pp. 2791-2795
Author(s):  
Qian Xiao ◽  
Yu Shan Jiang ◽  
Ru Zheng Cui
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Real Time ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Distributed Storage ◽  
Hopfield Neural Network ◽  
Lms Algorithm ◽  
The Neural Network ◽  
Simulation Results

Aiming at the large calculation workload of adaptive algorithm in adaptive filter based on wavelet transform, affecting the filtering speed, a wavelet-based neural network adaptive filter is constructed in this paper. Since the neural network has the ability of distributed storage and fast self-evolution, use Hopfield neural network to implement adaptive filter LMS algorithm in this filter so as to improve the speed of operation. The simulation results prove that, the new filter can achieve rapid real-time denoising.

scholarly journals Digital Data Processing Methods for Estimating Tractive Force of Tractors

2021 ◽  
Vol 31 (1) ◽  
pp. 127-142
Author(s):  
Vyacheslav F. Fedorenko ◽  
Vitaly E. Tarkivskiy ◽  
Nikolay P. Mishurov ◽  
Nikolay V. Trubitsyn
Keyword(s):  
Real Time ◽  
Strain Gauge ◽  
Impulse Noise ◽  
Median Filter ◽  
Digital Processing ◽  
Operating Conditions ◽  
Measuring Instruments ◽  
Important Indicator ◽  
Tractive Effort ◽  
Useful Signal

Introduction. When carrying out an energy assessment of agricultural machines and traction tests of tractors, the most important indicator is the value of the tractive effort. The existing methods for determining the tractive effort of tractors imply the use of specialized measuring instruments, such as strain gauges and devices for processing and displaying information. The accuracy of determining the tractive effort is significantly influenced by the physical and mechanical properties of soil. To process the useful signal during the measurement of tractive effort, the data stream of the strain gauge sensor must be subjected to additional digital filtering taking into account the operating conditions of the agricultural unit. Materials and Methods. The functions of changing the tractive effort obtained on the K-744R2 tractor in various gears have been analyzed. An algorithm for digital processing of the signal of a strain gauge force meter based on a median filter has been developed that makes it possible to increase the measurement accuracy. The advantage of the proposed method is the ability to cut off sharp short-term impulse noise and sharp fluctuations in the amplitude of the measured value. Results. A method for determining the amount of tractive effort using median signal processing has been proposed. A device for determining the tractive effort during testing of agricultural tractors and units has been developed. The choice of the main components of the device for determining the magnitude of the tractive effort has been substantiated. As a result of the research, a device for measuring and digital processing of the signal of a force meter based on a microcontroller and specialized software for processing initial data in real time was designed and manufactured. Discussion and Conclusion. The developed method makes it possible to exclude the negative effect of impulse noise arising in the process of measuring the tractive effort of the tractor. The proposed device for measuring the tractive effort of tractors is compatible at the level of the exchange protocol with existing devices, has a high speed of operation in real time, multi-channel operation.

scholarly journals Blind Source Separation Based on Quantum Slime Mould Algorithm in Impulse Noise

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Zhiwei Zhang ◽  
Hongyuan Gao ◽  
Jingya Ma ◽  
Shihao Wang ◽  
Helin Sun
Keyword(s):  
Objective Function ◽  
Blind Source Separation ◽  
Impulse Noise ◽  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Moving Average ◽  
Source Separation ◽  
Hybrid Optimization ◽  
Slime Mould ◽  
Stable Performance

In order to resolve engineering problems that the performance of the traditional blind source separation (BSS) methods deteriorates or even becomes invalid when the unknown source signals are interfered by impulse noise with a low signal-to-noise ratio (SNR), a more effective and robust BSS method is proposed. Based on dual-parameter variable tailing (DPVT) transformation function, moving average filtering (MAF), and median filtering (MF), a filtering system that can achieve noise suppression in an impulse noise environment is proposed, noted as MAF-DPVT-MF. A hybrid optimization objective function is designed based on the two independence criteria to achieve more effective and robust BSS. Meanwhile, combining quantum computation theory with slime mould algorithm (SMA), quantum slime mould algorithm (QSMA) is proposed and QSMA is used to solve the hybrid optimization objective function. The proposed method is called BSS based on QSMA (QSMA-BSS). The simulation results show that QSMA-BSS is superior to the traditional methods. Compared with previous BSS methods, QSMA-BSS has a wider applications range, more stable performance, and higher precision.

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