• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.461-466
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• 2013

As the technology of the digital information age has developed rapidly, lots of research has been done on the digital image processing techniques, such as the image restoration. However, the SM(Standard Median) filter is a typical method of recovering the image which are corrupted by the impulse noise, this method will also reduce the quality of image by generating an error in the edge region. In this paper, in order to restore the corrupted images in the impulse noise environment, a modified median filter algorithm is proposed, which uses the pixels as the center and takes double mask. By using the double mask, we are succeeded in acquiring the excellent performance on noise-canceling, edge preservation, and also in improving the quality of image.

• Journal of Broadcast Engineering
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• v.6 no.2
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• pp.139-147
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• 2001

Since various noises degrade not only image quality but also compression efficiency in MPEG and H.263, pre-processing is necessary to reduce spatial and temporal noise and to increase ceding efficiency as well. In this paper, we propose a simplified method for noise detection, spatial and temporal noise reduction. Noise detection is based on correlation of the current pixel with its neighboring 4 pixels. Spatial noose reduction utilizes a non-rectangular median filter that is less complex than the conventional rectangular median filter. The proposed temporal filter is an IIR average filter using LUT(Look-up Table) to enhance subjective video quality. The proposed pre-processing method is very simple and efficient.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1773-1778
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• 2012

Nowadays, the high quality of image is required with the demand for digital image processing devices is rapidly increasing. But image always damaged by many kinds of noises and it is necessary to remove noise and the denoising becomes one of the most important fields. In many cases image is corrupted by AWGN(additive white Gaussian noise). In this paper, we proposed an improved denoising algorithm with edge preservation. The proposed algorithm averages values processed by spatial weighted filter and self adaptive weighted filter. Then we add the value which is computed by the equation considering variance of mask and the estimated noise variance. Through the experience, the proposed filter performs well on noise suppression and edge preservation properties and improves the image visual quality.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.86-91
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• 2004

It is very important to detect the bearing defects in rotating machinery since the critical failure of bearing cause a machinery shutdown. However it is difficult to detect the vibration signal resulting from the initial defects of bearing because of the high level of broadband noise. A signal processing technique, called the adaptive line enhancer(ALE) as one of adaptive filter, is studied in this work. This technique is to eliminate broadband noise without a prior knowledge of the noise and signal characteristics. Also we propose the optimal methods for selecting the three main ALE parameters such as correlation length, filter order and adaptation constant used in the adaptative process. Vibration signals for three abnormal bearings, including inner and outer raceways and ball defects, were acquired from Anderon(angular derivative of radius on)meter. The experimental results showed that the proposed technique can reliably detect the bearing defective signals masked by broadband noise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.113-122
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• 2016

In this paper, we suggest a approach which comprises fast Fourier transform inversion by wavelet noise attenuation. It represents an inverse filtering by adopting a factor into the Wiener filtering, and the optimal factor is chosen to minimize the overall mean squared error. in order to apply the Wiener filter, we have to compute the power spectrum of original image from the corrupted figure. Since the Wiener filtering contains the inverse filtering process, it expands the noise when the blurring filter is not invertible. To remove the large noises, the best is to remove the noise using wavelet threshold. Wavelet noise attenuation steps are consisted of inverse filtering and noise reduction by Wavelet functions. experimental results have not outperformed the other methods over the overall restoration performance.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.45-55
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• 1999

In this paper, we used the WLMS(Wavelet domain Least Mean Square) adaptive filter based on the wavelet transform to cancel grain noise. Usually, grain noise occurs in changes of the crystalline structure of metals in high temperature environment. It makes the detection of flaw difficult. The WLMS adaptive filtering algorithm establishes the faster convergence rate by orthogonalizaing the input vector of adaptive filter as compared with that of LMS adaptive filtering algorithm in time domain. We implemented the WLMS adaptive filter by using the delayed version of the primary input vector as the reference input vector and then implemented the CA-CFAR(Cell Averaging- Constant False Alarm Rate) threshold estimator. CA-CFAR threshold estimator enables to detect the flaw and back echo signals automatically. Here, we used the output signals of adaptive filter as its input signal. To Cow the statistical characteristic of ultrasonic signals corrupted by grain noise, we performed run test. The results showed that ultrasonic signals are nonstationary signal, that is, signals whose statistical properties vary with time. The performance of each filter is appreciated by the signal-to-noise ratio. After LMS adaptive filtering in time domain, SNR improves to about 2-3㏈ but after WLMS adaptive filtering in wavelet domain, SNR improves to about 4-6㏈.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1185-1198
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• 1992

In this paper, the differential weighted algorithm proposed in order to improve th noise smoothing characteristics of conventional Median filter and FIR-Median Hybrid filter. Performance of some image restoration filter(median filter, FIR-Median Hybird filter, FIR-Median Hybrid filter to proposed differential weighted algorithm) are compared and evaluated on the noise smoothing characteristics and sharp edge conservation characteristics. Test and Real images used in this paper are Lenna and Urological images corrupted by impulse, gaussian, exponential and laplacian noise. Experimental results show that the FIR-Median Hybrid filter applied to the differential weighted algorithm are comparatively superior to others. But the filter orders have increased, the more time consumed to image processing. Hence if the adequate filtering by the type of image is selected. now after a great support will be take consideration into the various parts of application by computer science and of medical image processing.

• Journal of radiological science and technology
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• v.26 no.2
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• pp.63-69
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• 2003

Filtering is necessary to reduce statistical noise and to increase image quality in SPECT images. Noises controled by low-pass filter designed to suppress high spatial frequency in SPECT image. Most SPECT filter function control the degree of high frequency supression by chosing a cut of frequency. The location of cut off frequency determines the affect image noise and spatial resolution. If select the low cut off frequency, its provide good noise suppression but insufficient image quantity and high cut off frequencies increase the image resolution but insufficient noise suppression. The purpose of this study was to determines the optimam cut off level with comparison of FWHM according to cut off level in each kiters-Band-limited, Sheep-logan, Sheep-logan Hanning, Generalized Hamming, Low pass cosine, Parazen and Butterworth filter in SPECT camera. We recorded image along the X, Y, Z-axis with $^{99m}TcO_4$ point source and measured FWHM by use profile curve. We find averaged length is $9.16\;mm{\sim}18.14\;mm$ of FWHM in X, Y, and Z-axis, and Band-limited and Generalized Hamming filters measures 9.16 mm at 0.7 cycle/pixel cut off frequency.

• Journal of the Korea Convergence Society
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• v.4 no.4
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• pp.41-48
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• 2013

Observer design for system with unknown input was carried out. First, Kalman filter was considered to estimate system state with White noise. With the results of Kalman filter design, state observer, controller properties, including controllability and observability, and the Kalman filter structure and algorithm were also studied. Kalman filter algorithm was applied to Position and velocity measurement based on Kalman filter with white noise, and it was constructed and achieved by programming based on Matlab programming. Finally, observer for system with unknown input was constructed with the help of Gershgorin's disc theorem. With the designed observer, system states was constructed and applied to system with unknown input. By simulation results, estimation performance was verified. In this project, state feedback control theory, observer theory and relevant design procedure, as well as Kalman filter design were understood and used in practical application.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.1
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• pp.29-35
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• 2016

This paper presents an analysis of the short-range radar noise adjusting the angle of the radar reflector for the handicapped aids and suggests a complementary filter that combines a moving average filter with a heuristic algorithm to remove the radar noise. It also shows the effectiveness of the suggested filter by comparing the experiments results between the Kalman filter and the suggested filter.