• Title/Summary/Keyword: 복합 잡음

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The Performance Analysis of Multi-Level Quadrature Partial Response Signaling System (다치 직교 Partial Response Signaling 시스템의 특성에 관한 연구)

  • 이광열;고봉진;조성준
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.13 no.4
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    • pp.285-301
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    • 1988
  • The symbol error rate equations of multi-level quadrature PRS(QPRS) system have been derived in the individual and composite environment of Gaussian/impulsive noise, cochannel CW interference, carrier offset, phase jitter and fading. And using the derived error rate equations, the probability of error has been evaluated and shown in graphs as functions of carrier to noise power ratio, carrier to interference power ratio, phase error, impulsive index, the ration of Gaussian noise to impulsive noise power component, signal to noise power ration in phase locked loop(PLL), and fading figures. The rseults show that the error rate performances are generally more more degraded by impulsive noise than by Gaussian noise. But on the contrary the erors occurred more frequently by Gaussian noise than impulsive noise in a fading environment.

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Image Restoration Filter using Combined Weight in Mixed Noise Environment (복합잡음 환경에서 결합가중치를 이용한 영상복원 필터)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.210-212
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    • 2021
  • In modern society, various digital equipment are being distributed due to the influence of the 4th industrial revolution, and they are used in a wide range of fields such as automated processes, intelligent CCTV, medical industry, robots, and drones. Accordingly, the importance of the preprocessing process in a system operating based on an image is increasing, and an algorithm for effectively reconstructing an image is drawing attention. In this paper, we propose a filter algorithm based on a combined weight value to reconstruct an image in a complex noise environment. The proposed algorithm calculates the weight according to the spatial distance and the weight according to the difference between the pixel values for the input image and the pixel values inside the filtering mask, respectively. The final output was filtered by applying the join weights calculated based on the two weights to the mask. In order to verify the performance of the proposed algorithm, we simulated it by comparing it with the existing filter algorithm.

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Nonlinear Composite Filter for Gaussian and Impulse Noise Removal (가우시안 및 임펄스 잡음 제거를 위한 비선형 합성 필터)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.3
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    • pp.629-635
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    • 2017
  • In this paper, we proposed a nonlinear synthesis filter for noise reduction to reduce the effects of Gaussian noise and impulse noise. When the centralization of the local mask is judged to be Gaussian noise by the noise judgment, the weight value of the weight filter are applied differently according to the spatial weight filter and the pixel change by using the sample variance in the local mask. And if it is determined as the impulse noise, we proposed an algorithm that applies different weights of local histogram weight filter and standard median filter according to noise density of mask. In order to evaluate the performance of the proposed filter algorithm, we used PSNR(peak signal to noise ratio) and compared existing methods and proposed filter algorithm in the mixed noise environment with Gaussian noise, impulsive noise, and two noises mixed.

Noise Reduction Algorithm using Average Estimator Least Mean Square Filter of Frame Basis (프레임 단위의 AELMS를 이용한 잡음 제거 알고리즘)

  • Ahn, Chan-Shik;Choi, Ki-Ho
    • Journal of Digital Convergence
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    • v.11 no.7
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    • pp.135-140
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    • 2013
  • Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

Cochannel Interference Probability of Cellular Mobile Radio Systems in the Environments of Noise and Nakagami Fading plus Lognormal Shadowing (잡음, 나카가미 페이딩과 대수정규 shadowing이 존재하는 환경하에서 셀룰라 이동 무선 시스템의 동일 채널 간섭 확률)

  • 심용회;조성언;조성준
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.9
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    • pp.1668-1679
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    • 1994
  • The cochannel interference probability has been estimated both in the environment of Nakagami fading and Gasussian noise and in the environments of Gaussian noise and Nakagami fading plus log-normal shadowing. In noise and Nakagami fading environments, a theoretical analysis has been performed in order to calculate the cochannel interference probability in addition to computer simulation. In the environments of noise and Nakagami fading plus shadowing, only a simulation technique is used due to complexity in analysis. The spectrum efficiency is discussed on each case.

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Convergence Performance Evaluation of Radiation Protection for Apron using the PSNR (최대 신호 대 잡음비를 이용한 방사선 방어용 앞치마의 융복합 성능평가)

  • Kim, Dae-Ho;Kim, Sang-Hyun
    • Journal of Digital Convergence
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    • v.13 no.10
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    • pp.377-383
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    • 2015
  • This study evaluates the convergence radiation protection performance by measuring the PSNR(peak signal-to-noise ratio) values of the image J in the image evaluation program based on increased relative to this exposure of radiation workers.The aim of this study was to evaluate radiation protection performance of apron for design of it's basic information. Method was used to PSNR of Image J program and good condition apron was more than 27dB, the PSNR value of poor condition apron appeared to be less than 24dB. The result is the normality were satisfied distribution and T-test values were statistically significant with p<0.001. Results of evaluation of the performance protective apron through the more easily accessible experimental conditions and methods in the clinical was confirmed distinctly different. in order to reduce the radiation exposure we need to evaluate convergence protection performance and to be having a good performance apron.

Noise Removal Method using Entropy in High-Density Noise Environments (고밀도 잡음 환경에서 엔트로피를 이용한 잡음 제거 방법)

  • Baek, Ji-Hyeon;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.10
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    • pp.1255-1261
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    • 2020
  • Currently, the spread of mobile devices is gradually increasing. Accordingly, various techniques using images or photos are actively being researched. However, image data generates noise for complex reasons, and the accuracy of image processing increases according to the performance of removing noise. Therefore, noise reduction is one of the essential steps. Salt and pepper noise is a typical impulse noise in the image, and various studies are being conducted to remove the noise. However, existing algorithms have poor noise rejection performance in high frequency areas, and average filters have blurring. Therefore, in this paper, we propose an algorithm that effectively removes salt and pepper noise in the high frequency region as well as the low frequency region using entropy. For objective and accurate judgment of proposed algorithms, MSE and PSNR were used to compare and analyze existing algorithms.

A Filter Algorithm using Noise Component of Image in Mixed Noise Environments (복합 잡음 환경에서 영상의 잡음 성분을 이용한 필터 알고리즘)

  • Cheon, Bong-Won;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.8
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    • pp.943-949
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    • 2019
  • As use of digital equipment in various fields is increasing importance of processing video and signals is rising as well. However, in the process of sending and receiving signals, noise occurs due to different reasons and this noise bring about a huge influence on final output of the system. This research suggests algorithm for effectively repairing video in consideration to characteristics of its noise in condition where impulse and AWGN noises are combined. This algorithm tries to preserve video features by considering inference to noise components and resolution of filtering mask. Depending on features of input resolution, standard value is set and similar resolutions is selected for noise removal. This algorithm showing simulation result had outstanding noise removal and is compared and analyzed with existing methods by using different ways such as PSNR.

A Study on Denoising for Impulse and Gaussian Noise Images in Digital Images (임펄스 및 가우시안 잡음영상에서 잡음제거에 관한 연구)

  • Long, Xu;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.779-781
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    • 2013
  • As the demand for various multimedia service increases the technology that utilizes image as information transfer method develops rapidly. Though average filter, median filter and weight filter etc. have been proposed to remove various noises that are added to images, the existing methods are short of noise removal and edge reservation performance. Therefore, in this paper an algorithm, in which noise is decided at the first hand, and then it is processed through modified median filter and adaptive weighted average filter, is proposed to effectively remove the complex noise that has been added to an image. And it was compared with existing methods through simulation and PSNR(peak signal to noise ratio) has been used as a criterion.

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