• 제목/요약/키워드: noise reduction algorithm

검색결과 514건 처리시간 0.98초

Performance evaluation of noise reduction algorithm with median filter using improved thresholding method in pixelated semiconductor gamma camera system: A numerical simulation study

  • Lee, Youngjin
    • Nuclear Engineering and Technology
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    • 제51권2호
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    • pp.439-443
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    • 2019
  • To improve the noise characteristics, software-based noise reduction algorithms are widely used in cadmium zinc telluride (CZT) pixelated semiconductor gamma camera system. The purpose of this study was to develop an improved median filtering algorithm using a thresholding method for noise reduction in a CZT pixelated semiconductor gamma camera system. The gamma camera system simulated is a CZT pixelated semiconductor detector with a pixel-matched parallel-hole collimator and the spatial resolution phatnom was designed with the Geant4 Application for Tomography Emission (GATE). In addition, a noise reduction algorithm with a median filter using an improved thresholding method is developed and we applied our proposed algorithm to an acquired spatial resolution phantom image. According to the results, the proposed median filter improved the noise characteristics compared to a conventional median filter. In particular, the average for normalized noise power spectrum, contrast to noise ratio, and coefficient of variation results using the proposed median filter were 10, 1.11, and 1.19 times better than results using conventional median filter, respectively. In conclusion, our results show that the proposed median filter using improved the thresholding method results in high imaging performance when applied in a CZT semiconductor gamma camera system.

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

  • 최재승
    • 한국전자통신학회논문지
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    • 제8권9호
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    • pp.1293-1298
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    • 2013
  • 본 논문에서는 음성신호를 개선할 목적으로 잡음으로 오염된 음성신호로부터 잡음성분을 제거하기 위한 위너 필터를 사용한 잡음제거 알고리즘을 제안한다. 제안한 알고리즘은 먼저 잡음 복원 및 제거 방법에 기초하여 잡음으로 오염된 신호로부터 각 프레임에서 백색잡음의 잡음 스펙트럼을 제거한다. 또한 본 알고리즘은 선형예측 분석 방법에 기초한 위너 필터를 사용하여 음성신호를 강조한다. 본 실험에서는 일본 남성화자에 의한 음성과 잡음데이터를 사용하여 본 알고리즘의 실험 결과를 나타낸다. 백색잡음에 의하여 오염된 음성신호에 대하여 스펙트럼 왜곡률 척도를 사용하여 본 알고리즘이 유효하다는 것을 확인한다. 실험으로부터 백색잡음에 대하여 이전의 위너 필터와 비교하여 최대 4.94 dB의 출력 스펙트럼 왜곡률이 개선된 것을 확인할 수 있었다.

FXLMS 알고리즘을 이용한 3 차원 인클로저 시스템의 능동소음제어 (Active Noise Control of 3D Enclosure System using FXLMS Algorithm)

  • 오재응;양인형;윤지현;정재은;이종원
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2009년도 추계학술대회 논문집
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    • pp.240-241
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    • 2009
  • The method of the reduction of the duct noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the Least-Mean-Square (LMS) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system.

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Experimental study of noise level optimization in brain single-photon emission computed tomography images using non-local means approach with various reconstruction methods

  • Seong-Hyeon Kang;Seungwan Lee;Youngjin Lee
    • Nuclear Engineering and Technology
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    • 제55권5호
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    • pp.1527-1532
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    • 2023
  • The noise reduction algorithm using the non-local means (NLM) approach is very efficient in nuclear medicine imaging. In this study, the applicability of the NLM noise reduction algorithm in single-photon emission computed tomography (SPECT) images with a brain phantom and the optimization of the NLM algorithm by changing the smoothing factors according to various reconstruction methods are investigated. Brain phantom images were reconstructed using filtered back projection (FBP) and ordered subset expectation maximization (OSEM). The smoothing factor of the NLM noise reduction algorithm determined the optimal coefficient of variation (COV) and contrast-to-noise ratio (CNR) results at a value of 0.020 in the FBP and OSEM reconstruction methods. We confirmed that the FBP- and OSEM-based SPECT images using the algorithm applied with the optimal smoothing factor improved the COV and CNR by 66.94% and 8.00% on average, respectively, compared to those of the original image. In conclusion, an optimized smoothing factor was derived from the NLM approach-based algorithm in brain SPECT images and may be applicable to various nuclear medicine imaging techniques in the future.

광학 현미경 영상 기반 시간 분해능이 향상된 비지역적 평균 노이즈 제거 알고리즘 가능성 연구 (Feasibility Study of Non Local Means Noise Reduction Algorithm with Improved Time Resolution in Light Microscopic Image)

  • 이영진;김지연
    • 한국방사선학회논문지
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    • 제13권4호
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    • pp.623-628
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    • 2019
  • 본 연구의 목적은 시간 분해능이 향상된 비지역적 평균 (fast non local means, FNLM) 노이즈 제거 알고리즘을 모델링하여 광학 현미경 영상에서의 적용 가능성을 확인하는 것이다. 이를 위해 실제 흰쥐 (mouse)의 첫째어금니 치아를 사용하여 영상을 획득한 후 기존에 널리 사용되고 있는 노이즈 제거 알고리즘과 제안하는 FNLM 알고리즘을 각각 적용하여 비교하였다. 정량적 평가는 대조도 대 잡음비 (contrast to noise ratio, CNR), 변동계수 (coefficient of variation, COV), 그리고 최근에 개발된 no reference 기반의 방법인 natural image quality evaluator (NIQE)와 Blind/referenceless image spatial quality evaluator (BRISQUE)를 사용하였다. 결과적으로 모든 정량적 평가 인자에서 제안하는 FNLM 노이즈 제거 알고리즘이 가장 우수한 값을 나타내었다. 특히나 치아의 전체적인 형태학적 영상을 분석할 수 있는 NIQE와 BRISQUE 인자는 원본영상에 비하여 각각 1.14와 1.12배 향상됨을 확인할 수 있었다. 결론적으로 소동물 치아 광학 현미경 영상에서의 FNLM 노이즈 제거 알고리즘의 유용성 및 가능성을 증명하였다.

Noise reduction in low-dose positron emission tomography with adaptive parameter estimation in sinogram domain

  • Kyu Bom Kim;Yeonkyeong Kim;Kyuseok Kim;Su Hwan Lee
    • Nuclear Engineering and Technology
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    • 제56권10호
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    • pp.4127-4133
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    • 2024
  • Noise reduction in low-dose positron emission tomography (PET) is a well-researched topic aimed at reducing patient radiation doses and improving diagnosis. Software-based noise reduction mainly improves the contrast between regions by reducing the variation of the acquired image. However, it should be performed under appropriate parameters to reduce discrimination. We propose a method that derives optimal noise-reduction parameters using the multi-scale structural similarity index measure and visual information fidelity, which are metrics for image quality assessment. Simulation and experimental studies demonstrated the viability of the proposed algorithm. The contrast-to-noise ratio value of the denoised reconstruction slice, which was used as the optimal parameter, increased approximately three times compared to that of the low-dose slice while preserving the resolution. The results indicate that the proposed method successfully predicted the parameters according to the noise-reduction algorithm and PET system conditions in the sinogram domain. The proposed algorithm should help prevent misdiagnosis and provide standardized medical images for clinical application by performing appropriate noise reduction.

Adaptive Noise Reduction Algorithm for an Image Based on a Bayesian Method

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Communications for Statistical Applications and Methods
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    • 제19권4호
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    • pp.619-628
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    • 2012
  • Noise reduction is an important issue in the field of image processing because image noise lowers the quality of the original pure image. The basic difficulty is that the noise and the signal are not easily distinguished. Simple smoothing is the most basic and important procedure to effectively remove the noise; however, the weakness is that the feature area is simultaneously blurred. In this research, we use ways to measure the degree of noise with respect to the degree of image features and propose a Bayesian noise reduction method based on MAP (maximum a posteriori). Simulation results show that the proposed adaptive noise reduction algorithm using Bayesian MAP provides good performance regardless of the level of noise variance.

PET/MR 영상에서의 팬텀을 활용한 노이즈 감소를 위한 변형된 중간값 위너필터의 적용 효율성 연구 (Efficiency of Median Modified Wiener Filter Algorithm for Noise Reduction in PET/MR Images: A Phantom Study)

  • 조영현;이세정;이영진;박찬록
    • 대한방사선기술학회지:방사선기술과학
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    • 제44권3호
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    • pp.225-229
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    • 2021
  • The digital image such as medical X-ray and nuclear medicine field mainly contains noise distribution. The noise degree in image degrades image quality. That is why, the noise reduction algorithm is efficient for medical image field. In this study, we confirmed effectiveness of application for median modified Wiener filter (MMWF) algorithm for noise reduction in PET/MR image compared with median filter image, which is used as conventional noise redcution algorithm. The Jaszczak PET phantom was used by using 18F solution and filled with NaCl+NiSO4 fluids. In addition, the radioactivity ratio between background and six spheres in the phantom is maintained to 1:8. In order to mimic noise distribution in the image, we applied Gaussian noise using MATLAB software. To evlauate image quality, the contrast to noise ratio (CNR) and coefficient of variation (COV) were used. According to the results, compared with noise image and images with MMWF algorithm, the image with MMWF algorithm is increased approximately 33.2% for CNR result, decreased approximately 79.3% for COV result. In conclusion, we proved usefulness of MMWF algorithm in the PET/MR images.

광학 현미경 영상 화질개선의 추세에 관한 체계적 고찰 (A Systematic Review of Trends for Image Quality Improvement in Light Microscopy)

  • 김규석;이영진
    • 대한방사선기술학회지:방사선기술과학
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    • 제46권3호
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    • pp.207-217
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    • 2023
  • Image noise reduction algorithm performs important functions in light microscopy. This study aims to systematically review the research trend of types and performance evaluation methods of noise reduction algorithm in light microscopic images. A systematic literature search of three databases of publications from January 1985 to May 2020 was conducted; of the 139 publications reviewed, 16 were included in this study. For each research result, the subjects were categorized into four major frameworks-1. noise reduction method, 2. imaging technique, 3. imaging type, and 4. evaluation method-and analyzed. Since 2003, related studies have been conducted and published, and the number of papers has increased over the years and begun to decrease since 2016. The most commonly used method of noise reduction algorithm for light microscopy images was wavelet-transform-based technology, which was mostly applied in basic systems. In addition, research on the real experimental image was performed more actively than on the simulation condition, with the main case being to use the comparison parameter as an evaluation method. This systematic review is expected to be extremely useful in the future method of numerically analyzing the noise reduction efficiency of light microscopy images.