• ETRI Journal
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• v.46 no.4
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• pp.619-632
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• 2024

Medical signal processing requires noise and interference-free inputs for precise segregation and classification operations. However, sensing and transmitting wireless media/devices generate noise that results in signal tampering in feature extractions. To address these issues, this article introduces a finite impulse response design based on a two-level transpose Vedic multiplier. The proposed architecture identifies the zero-noise impulse across the varying sensing intervals. In this process, the first level is the process of transpose array operations with equalization implemented to achieve zero noise at any sensed interval. This transpose occurs between successive array representations of the input with continuity. If the continuity is unavailable, then the noise interruption is considerable and results in signal tampering. The second level of the Vedic multiplier is to optimize the transpose speed for zero-noise segregation. This is performed independently for the zero- and nonzero-noise intervals. Finally, the finite impulse response is estimated as the sum of zero- and nonzero-noise inputs at any finite classification.

• Journal of Advanced Marine Engineering and Technology
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• v.18 no.2
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• pp.75-82
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• 1994

The existence of peroodic impulse noises in distribution line carrier (DLC) communication system is known to be the most serious obstacle for improving DLC communication quality in reliability and capacity. From the spectral points, impulse noises can be divided into baseband type and modulation type the noise width of whichs are much different each other. With each nose type, this study presents the basic characteristics in relation to what they originate from and how their spectrum properties are revealed. The baseband type impulse noise is normally caused from thyristor circuit running with low switching speed and the modulation type noise from the circuit of switching power supply. The base wave of modulation noise is shown to be the pulsuatic charging current to primary condenser in switching power circuit. The study result indicates also that placing the DLC carrier frequency away the band predominated by modulated noise especially from RCC type switching power circuit is very important in DLC design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.798-800
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• 2014

In recent years, according to the improvement of Digital image technology have been recently developed most of communication technology from multimedia communication service as well as image data transmission. But In the process of storing and transmitting noise is still generated in noise and the image degrades rapidly quality of a lot of image impulse noise. To eliminate this noise, SMF, CWMF, SWMF etc. The filters have been proposed to interfere with the noise characteristics of the filter are somewhat sufficient. Therefore, in this paper, in order to remove impulse noise is proposed a modified median filter. And impulse noise removal algorithms to confirm the existed PSNR(peak signal to noise ratio) from using conventional methods were compared.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.336-340
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• 2011

Many approaches to image restoration are aimed at removing either gauss or impulse noise. This is because both types of degradation processes are distinct in nature, and hence they are easier to manage when considered separately. Nevertheless, it is possible to find them operating on the same image, which produces a hard damage. This happens when an image, already contaminated by Gaussian noise in the image acquisition procedure, undergoes impulsive corruption during its digital transmission. Here we proposed an algorithm first judge the type of the noise according to the difference values of pixel's neighborhood region and impulse noise's characteristic. Then removes the gauss noise by modified weighted mean filter and removes the impulse noise by modified nonlinear filter. The result of computer simulation on test images indicates that the proposed method is superior to traditional filtering algorithms. The proposed method can not only remove mixed noise effectively, but also preserve image details.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.80-85
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• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.71-74
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• 2005

This experimental study describes the propagation characteristics and reduction of impulse noises emitted from a high voltage COS(Cut Out Switch) fuse of a transformer. When a high voltage COS fuse becomes a short circuit by the over current. The peak sound Pressure above 150dB(A) is generated. In this study, an impulse noise generator is designed for generating the impulse noises similar to the noise level of COS fuse, which is utilized to test the noise reduction of a reactive silencer. The reactive silencers have been tested for 10 different types with each different porosity, hole diameter and length. From the experimental results, it is found that the reactive silencer has an excellent performance to greatly suppress the impulse noise and that its performance is closely connected with the porosity and hole diameter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3873-3887
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• 2018

In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.347-352
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• 2013

In impulse noise filtering techniques window size play an important role. Usually, an appropriate window is determined according to the noise density. A small window may not be able to suppress noise properly whereas a large window may remove edges and fine image details. Moreover, the value of the central pixel is estimated by considering all pixels within the window. In this work, contrary to the previous approaches, we propose an iterative impulse noise removal scheme that emphasizes on noise-free pixels within a small neighborhood. The iterative process continues until all noisy pixels are replaced with the estimated pixels. In order to estimate the optimal value for a noisy pixel, a genetic programming (GP) based estimator is evolved that takes few noise-free pixels as input. The estimator is constituent of noise-free pixels, arithmetic operators and random constants. Experimental results show that theproposed scheme is capable of removing impulse noise effectively while preserving the fine image details. Especially, our approach has shown effectiveness against high impulse noise density.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.1001-1004
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• 2006

Many researches have been processed to reconstruct corrupted an image by noise in fields of signal processing such as image recognition and compute. vision, and AWGN(additive white gaussian noise) and impulse noise are representative. Impulse noise consists of fired-valued(salt & pepper) impulse noise and random-valued impulse noise, and non-linear filters such as SM(standard median) filters are used to remove this noise. But basic SM filters still generate many errors in edge regions of an image, and in order to overcome this problem a variety of methods have been researched. In this paper, we proposed an impulse noise removal algorithm which is superior to the edge preserving capacity. At this tine, after detecting a noise by using the noise detector, we applied a noise removal algorithm based on the min-max operation and compared the capacity with existing methods through simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.163-168
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• 2009

In this paper, We proposed the efficient method of cleaning impulse noise using mean shift segmentation. This method do its job for the pixel which is identified as impulse noise using mean shift segmentation instead of all pixel of image by the existing method. we found that the quality of image is improved by measuring the sum of square error in result image and impulse noise is cleaned efficiently by doing experiment.