• Title, Summary, Keyword: Noise Filter

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Mixed Noise Reduction Filters for CR Images (CR X선 영상의 복합잡음 감소에 관한 연구)

  • Min, Jung-Whan;Jeong, Hea-Won;Kim, Jung-Min
    • Journal of radiological science and technology
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    • v.30 no.1
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    • pp.1-6
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    • 2007
  • This study is to decrease compound noise in x-ray films. This study compared Signal to noise ratio(SNR), Peak signal to noise ratio(PSNR), Mean square error(MSE) to surface of the earth. In addition, we evaluated noise elimination effect according to the kernel size of Median filter. This experiments show that some filters are useful by finding image that is near in circle image comparing circle picture with each processed picture. In noise power value, when cutoff frequency was compared with other filters of cutoff frequency. Cutoff frequency of $2/3\pi{\sim}3/4\pi$ is good and it shows good SNR and PSNR. Therefore, it can display high filter effect. As Median Filter's Kernel size grows SNR value gets bigger, which shows better filter effect. Most pictures are distorted after filter application in medical treatment image. It is important to keep spatial resolution in most medical images. Visual estimation as well as quantitative indicators should be necessary for a better image.

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Speckle Noise Reduction for Ultrasonic Images Using Homomorphic Wavelet-based MMSE Filter (호모모르픽 웨이브렛 기반 MMSE 필터를 이용한 초음파영상의 스펙클 잡음 제거)

  • 박원용;장익훈;김남철
    • Proceedings of the IEEK Conference
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    • pp.679-682
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    • 2000
  • In this paper, a MMSE filter in homomorphic wavelet transform domain is proposed for restoring an ultrasonic images corrupted by speckle noise. In order to remove effectively the speckle noise which is a kind of multiplicative noise, speckle noise is transformed into a form of additive noise and then the additive noise is denoised through the MMSE filter in homomorphic wavelet transform domain. The proposed method shows much higher quality in terms of ISNR and subject quality.

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An Impulse Noise-Robust Wiener Filter

  • Park, Soon-Young
    • Proceedings of the Acoustical Society of Korea Conference
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    • pp.33-36
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    • 1992
  • In this paper we propose the impulse noise-robust Wiener filter based on a combination of Wiener and modified trimmed mean(MTM) filters. The robust Wiener filter uses the trimming operation of the MTM filter to replace the outliers with the median within the window and the new set of samples which can be considered as the random process with same mean are inputted into the following Wiener filter. We show that the robust Wiener filter is effective in frequency selective filtering of nonstationary signals while preserving signal edges with the rejection of impulse noise.

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INS/GPS Integration System Using Adaptive Filter with Estimating Measurement Noise Variance (측정잡음 분산추정 적응필터를 이용한 INS/GPS 결합 시스템)

  • Yu, Myeong-Jong
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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    • pp.688-693
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    • 2007
  • The INS/GPS integration system is designed by employing an adaptive filter that can estimate the measurement noise variance using the residual of the filter. To verify the efficiency of the proposed loosely-coupled INS/GPS integration system, simulation is performed by assuming that GPS information has large position errors. Simulation results show that the proposed integration system with the adaptive filter is more effective in estimating the position and attitude errors than those with the Extended Kalman Filter.

Local Adaptive Noise Cancellation for MCG Signals Based on Wavelet Transform (웨이브릿 변환을 기반으로 한 심자도 신호의 국소 적응잡음제거)

  • 김용주;박희준;원철호;이용호;김인선;김명남;조진호
    • Progress in Superconductivity
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    • v.5 no.1
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    • pp.26-30
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    • 2003
  • Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

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Median Filter Applying Segmented Local Mask in Salt and Pepper Noise Environment (Salt and Pepper 잡음 환경에서 세분화된 국부마스크를 적용한 메디안 필터)

  • Hong, Sang-Woo;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.922-924
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    • 2015
  • Recently, the image processing technologies using the public media such as the film, TV, camera and advertisement have been rapidly developed. However, the deterioration occurs with the image in the process of data processing, transmission and storage, and the typical cause of such deterioration is the salt and pepper noise. Typical filters to remove the salt and pepper noise include CWMF(center weighted median filter) and AMF(adaptive median filter) but such filters bring more or less insufficient characteristics of noise removal and visual error as the noise density gets higher. Thus, this paper proposed the median filter which applied the local mask segmented to 4 areas in order to remove the salt and pepper noise effectively and used PSNR(peak signal to noise ratio) as a criterion of judgment.

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Research on Noise Reduction Algorithm Based on Combination of LMS Filter and Spectral Subtraction

  • Cao, Danyang;Chen, Zhixin;Gao, Xue
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.748-764
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    • 2019
  • In order to deal with the filtering delay problem of least mean square adaptive filter noise reduction algorithm and music noise problem of spectral subtraction algorithm during the speech signal processing, we combine these two algorithms and propose one novel noise reduction method, showing a strong performance on par or even better than state of the art methods. We first use the least mean square algorithm to reduce the average intensity of noise, and then add spectral subtraction algorithm to reduce remaining noise again. Experiments prove that using the spectral subtraction again after the least mean square adaptive filter algorithm overcomes shortcomings which come from the former two algorithms. Also the novel method increases the signal-to-noise ratio of original speech data and improves the final noise reduction performance.

Edge Preserving Smoothing in Infrared Image using Relativity of Guided Filter

  • Kim, Il-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.12
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    • pp.27-33
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    • 2018
  • In this paper, we propose an efficient edge preserving smoothing filter for Infrared image that can reduce noise while preserving edge information. Infrared images suffer from low signal-to-noise ratio, low edge detail information and low contrast. So, detail enhancement and noise reduction play crucial roles in infrared image processing. We first apply a guided image filter as a local analysis. After the filtering process, we optimization globally using relativity of guided image filter. Our method outperforms the previous methods in removing the noise while preserving edge information and detail enhancement.

Noise Reduction Algorithm in Speech by Wiener Filter (위너필터에 의한 음성 중의 잡음제거 알고리즘)

  • Choi, Jae-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.9
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    • pp.1293-1298
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    • 2013
  • This paper proposes a noise reduction algorithm using Wiener filter to remove the noise components from the noisy speech in order to improve the speech signal. The proposed algorithm first removes the noise spectrums of white noise from the noisy signal based on the noise reshaping and reduction method at each frame. And this algorithm enhances the speech signal using Wiener filter based on linear predictive coding analysis. In this experiment, experimental results of the proposed algorithm demonstrate using the speech and noise data by Japanese male speaker. Based on measuring the spectral distortion (SD) measure, experiments confirm that the proposed algorithm is effective for the speech by contaminated white noise. From the experiments, the maximum improvement in the output SD values was 4.94 dB better for white noise compared with former Wiener filter.