• Title/Summary/Keyword: 위너 필터

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Color Laser Printer Forensics Algorithm through Analyzing Noise Characteristics Co-occurrence (인쇄기기별 노이즈 특성의 빈도 분석을 통한 컬러 레이저프린터 판별 알고리즘)

  • Jo, Hyun Wu;Lee, Hae-Yeoun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.11a
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    • pp.557-560
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    • 2010
  • 고성능의 보급형 디지털 영상장비와 레이저프린터의 보급으로 인해 인쇄물의 불법적인 위변조가 사회적 문제로 대두되고 있고, 관련 범죄 또한 증가하는 추세이다. 이에 따라 디지털 포렌식 기술에 기반한 촬영 및 인쇄기기 식별 기술들이 연구되고 있다. 본 논문에서는 인쇄기기별 특성에서 기인하는 인쇄물의 노이즈 특성을 이용해 인쇄기기를 판별하는 알고리즘을 제안한다. 이산 웨이블릿 변환과 위너 필터를 이용한 노이즈 특성 추출 방법을 설명하고, 추출된 노이즈 특성에서 명암도 동시발생 행렬을 계산하고 왜도, 첨도, 공분산, 상관계수의 특징을 추출하였다. 추출한 특징을 서포트 벡터 머신에 적용하여 디지털 인쇄기기의 제조사와 모델을 판별하였다. 제안한 알고리즘의 성능을 분석하기 위하여 7대 프린터에서 각 371장씩 출력된 총 2,597장 이미지로 실험하였고, 제안한 알고리즘이 기존 방법에 비하여 높은 정확률을 나타냄을 보였다.

Performance change of defect classification model of rotating machinery according to noise addition and denoising process (노이즈 추가와 디노이징 처리에 따른 회전 기계설비의 결함 분류 모델 성능 변화)

  • Se-Hoon Lee;Sung-Soo Kim;Bi-gun Cho
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.1-2
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    • 2023
  • 본 연구는 환경 요인이 통제되어 있는 실험실 데이터에 산업 현장에서 발생하는 유사 잡음을 노이즈로 추가하였을 때, SNR비에 따른 노이즈별 STFT Log Spectrogram, Mel-Spectrogram, CWT Spectrogram 총 3가지의 이미지를 생성하고, 각 이미지를 입력으로 한 CNN 결함 분류 모델의 성능 결과를 확인하였다. 원본 데이터의 영향력이 큰 0db 이상의 SNR비로 합성할 경우 원본 데이터와 분류 결과상 큰 차이가 존재하지 않았으며, 노이즈 데이터의 영향이 큰 0db 이하의 SNR비로 합성할 경우, -20db의 STFT 이미지 기준 약 26%의 성능 저하가 발생하였다. 또한, Wiener Filtering을 통한 디노이징 처리 이후, 노이즈를 효과적으로 제거하여 분류 성능의 결과가 높아지는 점을 확인하였다.

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Usefulness of Median Modified Wiener Filter Algorithm for Noise Reduction in Liver Cirrhosis Ultrasound Image (간경변 초음파 영상에서의 노이즈 제거를 위한 Median Modified Wiener Filter 알고리즘의 유용성)

  • Seung-Yeon Kim;Soo-Min Kang;Youngjin Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.6
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    • pp.911-917
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    • 2023
  • The method of observing nodular changes on the liver surface using clinical ultrasonography is useful for diagnosing cirrhosis. However, the speckle noise that inevitably occurs in ultrasound images makes it difficult to identify changes in the liver surface and echo patterns, which has a negative impact on the diagnosis of cirrhosis. The purpose of this study is to model the median modified Wiener filter (MMWF), which can efficiently reduce noise in cirrhotic ultrasound images, and confirm its applicability. Ultrasound images were acquired using an ACR phantom and an actual cirrhotic patient, and the proposed MMWF algorithm and conventional noise reduction algorithm were applied to each image. Coefficient of variation (COV) and edge rise distance (ERD) were used as quantitative image quality evaluation factors for the acquired ultrasound images. We confirmed that the MMWF algorithm improved both COV and ERD values compared to the conventional noise reduction algorithm in both ACR phantom and real ultrasound images of cirrhotic patients. In conclusion, the proposed MMWF algorithm is expected to contribute to improving the diagnosis rate of cirrhosis patients by reducing the noise level and improving spatial resolution at the same time.

Denoising the Gaussian Noise by the Bayes Techique (Bayes 기법에 의한 가우시안 잡음제거)

  • Woo, Chang-Yong;Park, Nam-Chun;Kim, Jae-Hwan;Joo, Chang-Bok;Shin, Wee-Jae;Lee, Sang-Hoon;Kim, Sung-Il
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2005.11a
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    • pp.217-220
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    • 2005
  • 베이시안 기법의 잡음제거는 사진정보를 모형화하여 베이스 정리에 의해 사후정보를 계산하는 방법이다. 웨이블릿 변환 영역에서 각 대역의 원 신호 히스토그램을 일반화된 라플라시안 분포로 모형화하여 사전정보로 사용가능하다. 잡음 신호의 히스토그램에서 모형을 추정하기 위해서는 잡음편차가 필요하다. 이 논문에서는 단조변환을 이용하여 웨이블릿 변환된 잡음신호 각 대역의 편차를 추정한 후 이 편차에 가중치를 적용하여 모수를 추정한 후 베이스 기법으로 잡음을 제거하였다. 그리고 그 결과를 위너필터에 의해 잡음제거 된 결과와 PSNR로 비교하였다.

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Self-Regularization Method for Image Restoration (영상 복원을 위한 자기 정규화 방법)

  • Yoo, Jae-Hung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.1
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    • pp.45-52
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    • 2016
  • This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.

The Features Extraction of Ultrasonic Signal to Various Type of Defects in Solid (고체내부의 결함형태에 따른 초음파 신호의 특징추출)

  • Shin, Jin-Seob;Jun, Kye-Suk
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.6
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    • pp.62-67
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    • 1995
  • In this paper, the features extraction of reflected ultrasonic signals from various type of defects existing in Al metal has been studied by digital signal processing. Since the reflected signals from various type of the defects are ambiguous in features distinction from effects of noise, Wiener filtering using AR (auto-regressive) technique and least-absolute-values norm method has been used in features extraction and comparison of signals. In this experiment, three types of the defect in aluminum specimen have been considered: a flat cut, an angular cut, a circular hole. And the reflected signal have been measured by pulse-echo methods. In the result of digital signal processing of the reflected signal, it has been found that the features extraction method have been effective for classification of the reflected signals from various defects.

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Vocabulary Recognition Model using a convergence of Likelihood Principla Bayesian methode and Bhattacharyya Distance Measurement based on Vector Model (벡터모델 기반 바타챠랴 거리 측정 기법과 우도 원리 베이시안을 융합한 어휘 인식 모델)

  • Oh, Sang-Yeob
    • Journal of Digital Convergence
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    • v.13 no.11
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    • pp.165-170
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    • 2015
  • The Vocabulary Recognition System made by recognizing the standard vocabulary is seen as a decline of recognition when out of the standard or similar words. The vector values of the existing system to the model created by configuring the database was used in the recognition vocabulary. The model to be formed during the search for the recognition vocabulary is recognizable because there is a disadvantage not configured with a database. In this paper, it induced to recognize the vector model is formed by the search and configuration using a Bayesian model recognizes the Bhattacharyya distance measurement based on the vector model, by applying the Wiener filter improves the recognition rate. The result of Convergence of two method's are improved reliability experiments for distance measurement. Using a proposed measurement are compared to the conventional method exhibited a performance of 98.2%.

A Unified Time-domain Channel Estimator for OFDM based Ubiquitous Broadband Access (OFDM 기반의 유비쿼터스 광대역 접속을 위한 단일화 시간영역 채널 추정기)

  • Seo, Jeong-Wook;Kwak, Jae-Min;Kim, Dong-Ku
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.47 no.1
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    • pp.19-24
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    • 2010
  • This paper proposes a unified time-domain channel estimator (UTD-CE) for ubiquitous wireless broadband access based on orthogonal frequency division multiplexing (OFDM) systems. As a part of a software radio platform for ubiquitous services, the proposed UTD-CE can be exploited with the simply changeable parameters, pilot symbols and pilot subcarriers allocation, which are usually different according to the system specifications such as IEEE802.11x WiFI, IEEE802.16x WiMAX, DMB, Media FLO, DVB-H, etc. Given the pilot information, the channel frequency responses (CFRs) of data subcarriers will be analogously estimated by Wiener filtering and discrete Fourier transform (DFT)-based interpolation in the UTD-CE. Simulation results indicate that the proposed method significantly outperforms the conventional time-domain channel estimator when the pilot information is changed.

Noise Reduction of medical X-ray Image using Wavelet Threshold in Cone-beam CT (Cone-beam CT에서 웨이브렛 역치값을 이용한 x-ray 영상에서의 노이즈 제거)

  • Park, Jong-Duk;Huh, Young;Jin, Seung-Oh;Jeon, Sung-Chae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.6
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    • pp.42-48
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    • 2007
  • In x-ray imaging system, two kinds of noises are involved. First, the charge generated from the radiation interaction with the detector during exposure. Second, the signal is then added by readout electronics noise. But, x-ray images are not modeled by Gaussian noise but as the realization of a Poisson process. In this paper, we apply a new approach to remove Poisson noise from medical X-ray image in the wavelet domain, the applied methods shows more excellent results in cone-beam CT.

Estimation of Surface Spectral Reflectance using A Population with Similar Colors (유사색 모집단을 이용한 물체의 분광 반사율 추정)

  • 이철희;서봉우;안석출
    • Journal of Korea Multimedia Society
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    • v.4 no.1
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    • pp.37-45
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    • 2001
  • The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evaluate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth Color Checker. As a result, the proposed method showed a lower mean square error between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

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