• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.70-72
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• 2009

In this paper, nonlinear active noise control(ANC) of a 3rd-order Volterra system, which is robust to background noise variation, is proposed along with a variable step-size Gauss-Seidel pseudo affine projection(VSSGS-PAP) algorithm. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance in a background noise variation environment, compared with the conventional methods for the nonlinear ANC.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.1001-1004
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• 2010

Acoustic feedback and background noise variation can degrade the performance of an active noise control (ANC) system. In this paper, nonlinear ANC using a non-parametric VSS-NLMS (or NPVSS-NLMS) algorithm and online feedback path modeling is proposed, whereby the conventional linear ANC with online acoustic feedback-path modeling is further extended to nonlinear Volterra ANC with a linear acoustic feedback path. In particular, the step-size of the NPVSS-NLMS algorithm is controlled to reduce the effect of background noise variation in the ANC system. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance compared with the conventional nonlinear ANC method.

• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.54-59
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• 2009

Seismic station of high noise level has difficulties detecting relatively weak ground motions due to small earthquakes or teleseismic events because earthquake detectability of seismic station depends on seismic noise level. To figure out the capability of earthquake detection of a seismic network, therefore, seismic noise level of each station also needs to be considered, including the distribution of seismic stations. Recently, it has been known that most of broadband seismic stations in South Korea have affected by cultural noise in the frequencies higher than 1 Hz and show diurnal variations of noise level. In order to analyze the effect of diurnal variation of seismic noise level on earthquake detectability, we used the result of background seismic noise level analysis of seismograms of 30 broadband stations of KIGAM and KMA from 2005 to 2007. This study shows that earthquakes greater than magnitude 2.4 occurring within the Korean Peninsula can be detected at night while those greater than magnitude 2.6 can be detected in the daytime.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.381-394
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• 2016

The several noise level estimation algorithms that have been developed for use in image processing and computer graphics generally exhibit good performance. However, there are certain special types of noisy images that such algorithms are not suitable for. It is particularly still a challenge to use the algorithms to estimate the noise levels of complex textured photographic images because of the inhomogeneity of the original scenes. Similarly, it is difficult to apply most conventional noise level estimation algorithms to images rendered by the Monte Carlo (MC) method owing to the spatial variation of the noise in such images. This paper proposes a novel noise level estimation method based on histogram modification, and which can be used for more accurate estimation of the noise levels in both complex textured images and MC-rendered images. The proposed method has good performance, is simple to implement, and can be efficiently used in various image-based and graphic applications ranging from smartphone camera noise removal to game background rendition.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

• Journal of Digital Contents Society
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• v.14 no.1
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• pp.117-124
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• 2013

This paper suggests the robust method of extraction for moving objects in illumination variation by using image sequence from an immovable camera. The most difficult part of the implication is the effect by illumination and noise. The object area is hardly estimated when the dusky area occurs in illumination variation by time change. This thesis describes the extraction of moving objects employed by Gaussian mixture model which is noise robust measure. Also, the report suggests the elimination method of illumination part in input image by the representative illumination image which is defined to minimize the illumination influence.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.9
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• pp.888-894
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• 2007

The speech sound is detected by the vibration measurement of the window glass. In this study, we investigate the effect of the disturbing waves by background noise and window shaker excitation on the speech intelligibility of the detected sound. Based upon Modulation Transfer Function(MTF), speech intelligibility of the sound is objectively estimated by Speech Transmission Index(STI) As the level of the disturbing wave varies, variation of the speech intelligibility is examined. Experimental result reveals how STI is influenced by the level and frequency characteristics of the disturbing wave. By using a customized window shaker for disturbing sound, we evaluate the efficiency and the frequency characteristics of the anti-eavesdropping system. The purpose of the study is to provide useful information to prevent the eavesdropping through the window glass.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.34-37
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• 2012

Purpose: To verify the optimal scan time per bed for clinical application, we evaluated the quality of $^{18}F$-FDG images with varying scan times in a phantom and 20 patients with 38 lesions using a Philips (TOF) PET/CT scanner. Materials and Methods: The PET/CT images of a NEMA IEC body phantom and 20 patients (16 males, 4 females) were acquired for 5 different scan times of 20-100 sec per bed with intervals of 20 sec. The activity ratio of hot spheres (diameter of 17 [H1], 22 [H2] and 28 [H3] mm) to the background region in the IEC body phantom was 8-to-1. The contrast recovery coefficient (CRC) and standard uptake value (SUV) based on ROIs of hot spheres and background region were calculated. The noise in each background region was estimated as the ratio of SD of counts to the mean counts in the background region. On the patient image, the injected dose of $^{18}F$-FDG was $444{\pm}74$ MBq and the SUVs in the 38 hot lesions were measured. Results: The two scan time groups (LT-60 [<60 sec] and GT-60 [${\geq}60$ sec]) were compared. In the phantom study, the coefficient of deviations (CVs, %) of CRC and SUV in LT-60 (H1: 14.2 and 7.3, H2: 11.4 and 7.8, H3: 4.9 and 3.2) were higher than GT-60 (H1: 8.9 and 2.8, H1: 8.2 and 5.0, H3: 2.0 and 1.6). In the patient study, the mean CV of CRC and SUV in LT-60 (4.0) was higher than GT-60 (1.2). Conclusion: This study showed that noise increased as the scan time decreased. High noise for the scan time <60 sec per bed yielded high variation of SUV and CRC. Therefore, considering PET/CT image quality, the scan time per bed in the TOF PET/CT scanner should be at least ${\geq}60$ sec.

• Journal of radiological science and technology
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• v.44 no.3
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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.