• Title/Summary/Keyword: Signal-to-noise ratio improvement

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A Note on Generalized Signal-to-Noise Ratios (일반적인 SN비에 관한 소고)

  • 임용빈;이영조
    • Journal of Korean Society for Quality Management
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    • v.25 no.4
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    • pp.88-98
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    • 1997
  • For quality improvement, it is important to reduce variations of the quality characteristic. That can be achieved by the a, pp.ication of parameter design methodology to make the performance of the quality characteristic robust over the variety of noise conditions. Taguchi has used the signal-to-noise ratios for that purpose. For the static target characteristic and the dynamic characteristic problem, we propose a reasonable generalized SN ratio and p-value plot for identifying dispersion factors. The orginal idea of the p-value plot in from the gamma-plot in Lunani, Nair & Wasserman(1995). The graphic advantage of the p-value polt for identifying dispersion factors is illustrated through constructed examples.

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An Adaptive Guided Filter for Performance Improvement of Aviation Image Fusion (항공 영상 융합의 성능 향상을 위한 적응 가이디드 필터)

  • Kim, Sun Young;Kang, Chang Ho;Park, Chan Gook
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.44 no.5
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    • pp.407-415
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    • 2016
  • In this paper, an aviation image fusion method is proposed for creating an informative fused image through gray scale images within noise. The proposed method is based on an adaptive guided filter which adjusts regulation parameter of the filter based on peak signal noise ratio (PSNR) in order to behave as an edge-preserving filtering property. Simulation results demonstrate that the proposed method preserves the edge information of the input image and reduces the noise effect while maintaining designed PSNR.

A Study on Removing Impulse Noise using Modified Adaptive Switching Median Filter (변형된 적응 스위칭 메디안 필터를 이용한 임펄스 잡음제거에 관한 연구)

  • Gao, Yinyu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.11
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    • pp.2474-2479
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    • 2011
  • As society has developed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized. However, image data is always corrupted by various noises during image processing, so researches for removing noises have been continued until now. In this paper, in order to remove impulse noise we proposed modified adaptive switching median filter that consists of two stages: noise detection and noise removal. Proposed algorithm only processes noise pixels and these noise pixels are replaced by filter output, so proposed algorithm performs well not only removes noise but also preserves edge information. Also we compare existing methods using PSNR(peak signal to noise ratio) as the standard of judgement of improvement effect and choose conventional algorithms to compare with our proposed method.

SNR Improvement in A Wireless Optical Differential Detector Using Plastic Fibers (플라스틱 광섬유를 이용한 무선광 차동검출기의 신호대잡음비 개선)

  • Lee Seong-Ho
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.16 no.4 s.95
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    • pp.410-417
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    • 2005
  • In this paper, optical noise is reduced by a differential detector with a plastic optical fiber bundle in a wireless optical interconnection. A plastic optical fiber bundle divides the received optical signal equally and connects it to two photodiodes. In this configuration two photodiodes effectively detect the optical signal at one point, and the output voltage variation due to the abrupt change of optical noise distribution in space disappears. The signal to noise ratio in a differential detector with a fiber bundle was improved to be $10\;\cal{dB}$ higher than in a single photodiode with an optical filter.

Speech Processing System Using a Noise Reduction Neural Network Based on FFT Spectrums

  • Choi, Jae-Seung
    • Journal of information and communication convergence engineering
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    • v.10 no.2
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    • pp.162-167
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    • 2012
  • This paper proposes a speech processing system based on a model of the human auditory system and a noise reduction neural network with fast Fourier transform (FFT) amplitude and phase spectrums for noise reduction under background noise environments. The proposed system reduces noise signals by using the proposed neural network based on FFT amplitude spectrums and phase spectrums, then implements auditory processing frame by frame after detecting voiced and transitional sections for each frame. The results of the proposed system are compared with the results of a conventional spectral subtraction method and minimum mean-square error log-spectral amplitude estimator at different noise levels. The effectiveness of the proposed system is experimentally confirmed based on measuring the signal-to-noise ratio (SNR). In this experiment, the maximal improvement in the output SNR values with the proposed method is approximately 11.5 dB better for car noise, and 11.0 dB better for street noise, when compared with a conventional spectral subtraction method.

A Fuzzy Impulse Noise Filter Based on Boundary Discriminative Noise Detection

  • Verma, Om Prakash;Singh, Shweta
    • Journal of Information Processing Systems
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    • v.9 no.1
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    • pp.89-102
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    • 2013
  • The paper presents a fuzzy based impulse noise filter for both gray scale and color images. The proposed approach is based on the technique of boundary discriminative noise detection. The algorithm is a multi-step process comprising detection, filtering and color correction stages. The detection procedure classifies the pixels as corrupted and uncorrupted by computing decision boundaries, which are fuzzified to improve the outputs obtained. In the case of color images, a correction term is added by examining the interactions between the color components for further improvement. Quantitative and qualitative analysis, performed on standard gray scale and color image, shows improved performance of the proposed technique over existing state-of-the-art algorithms in terms of Peak Signal to Noise Ratio (PSNR) and color difference metrics. The analysis proves the applicability of the proposed algorithm to random valued impulse noise.

Adaptation of Deep Learning Image Reconstruction for Pediatric Head CT: A Focus on the Image Quality (소아용 두부 컴퓨터단층촬영에서 딥러닝 영상 재구성 적용: 영상 품질에 대한 고찰)

  • Nim Lee;Hyun-Hae Cho;So Mi Lee;Sun Kyoung You
    • Journal of the Korean Society of Radiology
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    • v.84 no.1
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    • pp.240-252
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    • 2023
  • Purpose To assess the effect of deep learning image reconstruction (DLIR) for head CT in pediatric patients. Materials and Methods We collected 126 pediatric head CT images, which were reconstructed using filtered back projection, iterative reconstruction using adaptive statistical iterative reconstruction (ASiR)-V, and all three levels of DLIR (TrueFidelity; GE Healthcare). Each image set group was divided into four subgroups according to the patients' ages. Clinical and dose-related data were reviewed. Quantitative parameters, including the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and qualitative parameters, including noise, gray matter-white matter (GM-WM) differentiation, sharpness, artifact, acceptability, and unfamiliar texture change were evaluated and compared. Results The SNR and CNR of each level in each age group increased among strength levels of DLIR. High-level DLIR showed a significantly improved SNR and CNR (p < 0.05). Sequential reduction of noise, improvement of GM-WM differentiation, and improvement of sharpness was noted among strength levels of DLIR. Those of high-level DLIR showed a similar value as that with ASiR-V. Artifact and acceptability did not show a significant difference among the adapted levels of DLIR. Conclusion Adaptation of high-level DLIR for the pediatric head CT can significantly reduce image noise. Modification is needed while processing artifacts.

The Review of Exposure Index in Digital Radiography and Image Quality (디지털 영상에서 화질관리에 관한 노출지수(EI)의 유용성 연구)

  • Yang, Sook;Han, Jae Bok;Choi, Nam Gil;Lee, Seong Gil
    • Journal of Radiation Protection and Research
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    • v.38 no.1
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    • pp.29-36
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    • 2013
  • The aim of this study was to determine the correlation between exposure index (EI) and dose factors related to radiation dose optimization in digital radiography (DR) system. Two phantoms with built-in regional test object for quantitative assessment of images were used to produce image signals that acquired in chest radiography background. EI and entrane surface dose (ESD) increased proportionally with rise of radiation dose (kVp, mAs) in both DR and CR systems. Especially, DR detector was effective to form good contrast and hence, reached easily to improvement of image quality with minimal dose changes. It made operators possible to expect the accuracy of EI values deeply related to absorbed dose of the detector. The evaluation of images was obtained specially employed calculation of noise to signal ratio (NSR) and contrast to noise ratio (CNR). These measurements were performed for how exposure factors affect image quality. NSR was inversely proportional to kVp and mAs and low NSR represented high signal detection efficiency. Consequently, EI values was the measure of the amount of exposure received by the image receptor and it was proportional to exposure factors. Therefore the EI in a recommended range from manufacturer can offer optimal image quality. Also, continuous monitoring of EI values in the digital radiography can reduce the unnecessary patient dose and help the quality control of the system.

A Study on Improvement of MUAP Resolution using Spatial Filter (공간필터에 의한 운동단위 활동전위의 분해능 향상에 관한 연구)

  • Yang, Duck-Jin;Jun, Chang-Ik;Lee, Young-Suk;Lee, Jin;Kim, Sung-Hwan
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.1
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    • pp.55-64
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    • 2004
  • Conventional bipolar surface electromyography(EMG) technique detects only the superimposed electromyographic activity of a large number of motor units due to its low spatial resolution. For the diagnosis of neuromuscular disorder, the information of single MU is required. In this paper, 9 channel array surface electrode system was as designed and MLoG filter was proposed. Also the MCPT(modified convolution processing technique)method was proposed for the improvement of MUAP resolution. For performance evaluation, power spectrum analysis of random data and raw EMG signal comparison of MUAP shape and quantitative estimation of SNR were executed. As a result, the MUAP resolution improvement of 32% was obtained from the standpoint of the signal-to-noise ratio(SNR).

A New Smart Antenna Algorithm for Improving the Performance of CDMA Reverse Link (CDMA 역방향 링크의 성능 개선을 위한 스마트 안테나 수신기 알고리즘)

  • 안재민;안치준;임민중
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.4
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    • pp.45-53
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    • 2003
  • A new smart antenna receiver which incorporates the spatial fourier Transform and the maximal ratio combining(MRC) is proposed. By adapting the spatial fourier transform, the proposed method could separate the received signal into several spatial frequency components which correspond to the arrival angles of signal components, which means the beam focusing. By using the MRC, the proposed method could achieve the maximum signal to noise ratio for the signal of interest. The proposed algorithm is integrated to the CDMA reverse link receiver and simulations are performed to confirm the performance. As a result, the beam focusing effect is confirmed and the performance gain with the proposed algorithm is comparable to ordinary smart antenna receivers. The simulations are performed over the additive white gaussian noise (AWGN) environments and the results are obtained for the beam focusing capability according to the angle of arrival of a signal and the bit error performance improvement according to the number of combining branches in the MRC.