• 제목/요약/키워드: noise filtering

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Mixture Filtering Approaches to Blind Equalization Based on Estimation of Time-Varying and Multi-Path Channels

  • Lim, Jaechan
    • Journal of Communications and Networks
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    • 제18권1호
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    • pp.8-18
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    • 2016
  • In this paper, we propose a number of blind equalization approaches for time-varying andmulti-path channels. The approaches employ cost reference particle filter (CRPF) as the symbol estimator, and additionally employ either least mean squares algorithm, recursive least squares algorithm, or $H{\infty}$ filter (HF) as a channel estimator such that they are jointly employed for the strategy of "Rao-Blackwellization," or equally called "mixture filtering." The novel feature of the proposed approaches is that the blind equalization is performed based on direct channel estimation with unknown noise statistics of the received signals and channel state system while the channel is not directly estimated in the conventional method, and the noise information if known in similar Kalman mixture filtering approach. Simulation results show that the proposed approaches estimate the transmitted symbols and time-varying channel very effectively, and outperform the previously proposed approach which requires the noise information in its application.

반복적 최적 자승 학습에 기반을 둔 움직임 적응적 시간영역 잡음 제거 필터링 (Motion Adaptive Temporal Noise Reduction Filtering Based on Iterative Least-Square Training)

  • 김성득;임경원
    • 대한전자공학회논문지SP
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    • 제47권5호
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    • pp.127-135
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    • 2010
  • 동영상에 내재된 잡음을 제거하기 위해 사용되는 움직임 적응적 시간영역 잡음 제거 필터링에서는 움직임의 정도에 따라 필터링의 강도를 적절하게 조절하는 것이 매우 중요하다. 본 논문에서는 최적 자승 학습에 기반을 둔 움직임 적응적 시간영역필터링 방안을 제안한다. 움직임 정도에 따라 각 화소를 분류하여 분류코드를 지정하고, 각 분류코드에 따라 반복적 최적 자승학습에 기반을 둔 최적의 필터 계수를 유도한다. 반복적 학습과정은 사전에 미리 수행되어 학습된 결과만 룩업 테이블에 저장된다. 실제 잡음 제거 필터링 과정에서는 각 화소를 움직임 정도에 따라 분류한 후 분류코드에 따라 룩업 테이블에 있는 필터계수를 읽어 간결한 필터링을 취한다. 실험결과는 제안된 방법이 잡음 제거 응용에서 번짐을 방지하면서 동영상 잡음을 효과적으로 제거함을 보여준다.

SAP 잡음 제거를 위한 적응적 스위칭 필터링 알고리즘 (Adaptive Switching Filtering Algorithm for SAP noise)

  • 김동형
    • 디지털산업정보학회논문지
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    • 제18권1호
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    • pp.25-35
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    • 2022
  • The SAP(salt-and-pepper) noise changes the pixel value to the maximum and minimum values of the dynamic region of the pixel. For this reason, unlike white Gaussian noise, SAP noise can predict the ratio of noise relatively easily. Because the condition of the neighboring pixels that can be referenced changes according to the noise ratio, it is necessary to apply different noise reduction methods according to the noise ratio. This paper proposes an adaptive switching filtering algorithm which can eliminates the SAP noise. It consists of two phases. It first detects the location of the SAP noise and calculates the noise ratio. After that, the image is reconstructed using different methods depending on which of the three sections the calculated noise ratio belongs to. As a result of the experiment, the proposed method showed superior objective and subjective image quality compared to the previous methods such as MF, AFSWMF, NAMF and RWMF.

An Enhanced Clarity of Husky Voice by Dissonant Frequency Filtering

  • Kang, Sang-Ki;Baek, Seong-Joon
    • 음성과학
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    • 제12권4호
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    • pp.71-76
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    • 2005
  • There have been numerous studies on the enhancement of noisy speech signal. In this paper, we propose a new speech enhancement method, that is, a filtering of a dissonant frequency combined with noise suppression algorithm. The simulation results indicate that the proposed method provides a significant gain in voice clarity. Therefore if the proposed enhancement scheme is used as a pre-filter, the perceptual clarity of husky voice is greatly enhanced.

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A Study on the Enhanced Filtering for the Removal of BEMF in BLDC Motors

  • Moon, Yu-Sung;Choi, Jae-Hyun;Kim, Jung-Won
    • 전기전자학회논문지
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    • 제23권1호
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    • pp.310-313
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    • 2019
  • This paper used the majority function to digitally filter back-electromotive force as an explanation of the Brushless DC MOTOR control algorithm. The cause and improvement of motor noise, which are operating in close proximity to high frequency sources, did not use conventional low pass filter and comparator elements. Also, they repeatedly output a noise-free BEMF signal for the input value of the majority detection filtering. These filtering steps can help reduce costs and minimize the area of a PCB by requiring relatively little hardware.

A Method of Coupling Expected Patch Log Likelihood and Guided Filtering for Image De-noising

  • Wang, Shunfeng;Xie, Jiacen;Zheng, Yuhui;Wang, Jin;Jiang, Tao
    • Journal of Information Processing Systems
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    • 제14권2호
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    • pp.552-562
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    • 2018
  • With the advent of the information society, image restoration technology has aroused considerable interest. Guided image filtering is more effective in suppressing noise in homogeneous regions, but its edge-preserving property is poor. As such, the critical part of guided filtering lies in the selection of the guided image. The result of the Expected Patch Log Likelihood (EPLL) method maintains a good structure, but it is easy to produce the ladder effect in homogeneous areas. According to the complementarity of EPLL with guided filtering, we propose a method of coupling EPLL and guided filtering for image de-noising. The EPLL model is adopted to construct the guided image for the guided filtering, which can provide better structural information for the guided filtering. Meanwhile, with the secondary smoothing of guided image filtering in image homogenization areas, we can improve the noise suppression effect in those areas while reducing the ladder effect brought about by the EPLL. The experimental results show that it not only retains the excellent performance of EPLL, but also produces better visual effects and a higher peak signal-to-noise ratio by adopting the proposed method.

KERNEL-BASED NOISE FILTERING OF NEUTRON DETECTOR SIGNALS

  • Park, Moon-Ghu;Shin, Ho-Cheol;Lee, Eun-Ki
    • Nuclear Engineering and Technology
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    • 제39권6호
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    • pp.725-730
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    • 2007
  • This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests.

국부 통계를 이용한 메디안 필터의 적응 영상 복원 (Adaptive Image Restoration of Median Filter Using Local Statistics)

  • 김남철;윤장홍;황찬식
    • 대한전자공학회논문지
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    • 제24권5호
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    • pp.863-867
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    • 1987
  • When digital image signals are transmitted or stored, they may be usually degraded by impulsive noise such as BSC noise. Though median filtering is a very effective method to reduce the impulsive noise, it brings non-negligible distortion after filtering. Several algorithms have been proposed to reduce such a distortion, but their reconstructed image quality are inadequate in some cases and they have a difficulty in real-time processing. In this paper, an effective filtering algorithm which can not only reduce the noise effectively but also preserve the edges well and lessen the distortion greatly, is presented. The proposed algorithm is an adaptive algorithm of median filter using local statistics, based on the characteristics of human eyes. The adaptive algorithm results shwo performance improvement of up to 3-4 dB over the nonadaptive one.

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Stochastic Restoration and Reconstruction Filters for 2-D and 3-Dimensional Image Reconstruction

  • Yum, Young-Ho
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1979년도 하계 전자.전기연합학술발표회논문집
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    • pp.158-159
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    • 1979
  • Based on minimum-mean-sqare error criterion, a noise filtering algorithm for the reconstruction of an image function from noisy projection data is suggested. The filter is constructed with a few projection data. This algorithm requires less computational time compared with other noise filtering algorithm.

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Adaptive Switching Median Filter for Impulse Noise Removal Based on Support Vector Machines

  • Lee, Dae-Geun;Park, Min-Jae;Kim, Jeong-Ok;Kim, Do-Yoon;Kim, Dong-Wook;Lim, Dong-Hoon
    • Communications for Statistical Applications and Methods
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    • 제18권6호
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    • pp.871-886
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    • 2011
  • This paper proposes a powerful SVM-ASM filter, the adaptive switching median(ASM) filter based on support vector machines(SVMs), to effectively reduce impulse noise in corrupted images while preserving image details and features. The proposed SVM-ASM filter is composed of two stages: SVM impulse detection and ASM filtering. SVM impulse detection determines whether the pixels are corrupted by noise or not according to an optimal discrimination function. ASM filtering implements the image filtering with a variable window size to effectively remove the noisy pixels determined by the SVM impulse detection. Experimental results show that the SVM-ASM filter performs significantly better than many other existing filters for denoising impulse noise even in highly corrupted images with regard to noise suppression and detail preservation. The SVM-ASM filter is also extremely robust with respect to various test images and various percentages of image noise.