• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.883-885
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• 2013

Image restoration refers to removing different kinds of noise added to image, and to reducing effect of noise upon image. For image restoration, some methods such as mean filter, median filter and weighted filter were proposed, but the existing methods have poor denoising and edge-reserved performance. Therefore, in this paper modified median filter algorithm was proposed that enlarges mask size according to median value of mask in order to remove noise efficiently. And, it was compared by simulation to the existing methods, and MSE(mean squared error) was used on a criterion of evaluation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.779-781
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• 2013

As the demand for various multimedia service increases the technology that utilizes image as information transfer method develops rapidly. Though average filter, median filter and weight filter etc. have been proposed to remove various noises that are added to images, the existing methods are short of noise removal and edge reservation performance. Therefore, in this paper an algorithm, in which noise is decided at the first hand, and then it is processed through modified median filter and adaptive weighted average filter, is proposed to effectively remove the complex noise that has been added to an image. And it was compared with existing methods through simulation and PSNR(peak signal to noise ratio) has been used as a criterion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.150-156
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• 2007

Noise is generated by several causes, when signal is processed. Hence, it generates error in the process of data transmission and decreases recognition ratio of image and speech data. Therefore, after eliminating those noises, a variety of methods for reconstructing the signal have been researched. Recently, wavelet transform which has time-frequency localization and is possible for multiresolution analysis is applied to many fields of technology. Then threshold-and correlation-based methods are proposed for removing noise. But, conventional methods accept a lot of noise as an edge and are impossible to remove the additive white Gaussian noise (AWGN) and the impulse noise at the same time. Therefore, in this paper we proposed new wavelet-based algorithm for reconstructing degraded signal by noise and compared it with conventional methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.9
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• pp.979-986
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• 2010

This paper presents an algorithm for retrieving precise radar cross sections(RCS) of various trihedral corner reflectors (TCR) which are external calibrators of synthetic aperture radar(SAR) systems. The theoretical RCSs of the TCRs are computed based on the physical optics(PO), geometrical optics(GO), and physical theory of diffraction(PTD) techniques; that is, the RCS computation includes the single reflections(PO), double reflections(GO-PO), triple reflections(GO-GO-PO), and edge diffractions(PTD) from the TCR. At first, we acquire an SAR image of the area that five TCRs installed in, and then extract the RCS of the TCRs. The RCSs of the TCRs are extracted accurately from the SAR image by adding up the power spill, which is generated due to the radar IRF(Impulse Response Function), using a square window. We compare the extracted RCSs with the theoretical RCSs and analyze the difference between the theoretical and experimental RCSs of the TCR for various window sizes and various backscattering coefficient levels of the adjacent area. Finally, we propose the minimum size of the integration area and the maximum level of the backscattering coefficients for the adjacent area.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.2
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• pp.97-107
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• 2017

This study is the second investigation on the steady flow characteristics of an SI engine with a semi-edge combustion chamber as a function of the port shape with varying evaluation positions. For this purpose, the planar velocity profiles were measured from 1.75B, 1.75 times of bore position apart from the bottom of head, to 6.00B positions using particle - image velocimetry. The flow patterns were examined with both a straight and a helical port. The velocity profiles, streamlines, and centers of swirl were almost the same at the same valve lift regardless of the measuring position, which is quite different from the case of the pent-roof combustion chamber. All the eccentricity values of the straight port were out of distortion criterion 0.15 through the lifts and the position. However, the values of the helical port exceeded the distortion criterion by up to 4 mm lift, but decreased rapidly above the 3.00B position and the 5 mm lift. There always existed a relative offset effect in the evaluation of the swirl coefficient using the PIV method due to the difference of the ideal impulse swirl meter velocity profile assumption, except for the cylinder-center-base estimation that was below 4 mm of the straight port. Finally, it was concluded that taking the center as an evaluation basis and the assumption about the axial velocity profile did not have any qualitative effect on swirl evaluation, but affected the value owing to the detailed profile.

• 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 the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.285-294
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• 2004

Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

• The Transactions of the Korea Information Processing Society
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• v.6 no.7
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• pp.1980-1987
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• 1999

Restored image is always lower quality than original one due to distortion and noise. The purpose of image restoration is to improve the image quality by fixing the noise or distortion information. One category of spatial filters for image restoration is linear filter. This filter algorithm is easily implemented and can be suppressed the Gaussian noise effectively, but not so good performance for spot or impulse noise. In this paper, we propose the nonlinear spatial filter algorithm for image restoration called the optimal adaptive multistage filter(OAMF). The OAMF is used to reduce the filtering time, increases the noise suppression ratio and preserves the edge information. The OAMF optimizes the adaptive multistage filter(AMF) by using weight learning algorithm of back-propagation learning algorithm. Simulation results of this filter algorithm are presented and discussed.

• Journal of the Korean Society of Propulsion Engineers
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• v.19 no.3
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• pp.29-38
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• 2015

In this study, 3-dimensional URANS simulation was performed to analyze the effect of the nozzle-rotor axial gap spacing of a supersonic impulse turbine on turbine performance. The computations were conducted for four different axial gap cases corresponding to about 6%, 10%, 20% and 30% of the blade height, respectively. The results show a good agreement with previous studies and the turbine efficiency decreases drastically in certain range. It is examined that the turbine performance characteristics could change depending on the influence of leading edge shock to the nozzle outlet. It is also found that the entropy rise distributions along the span differ from each other.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.707-712
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• 2018

The number of CT examinations is increasing, and radiation exposure is also increasing. repeated tests can affect the lens and thyroid. In hospitals, there is a tendency to lack interest in major long-term radiation exposure compared to the interest in increasing image information and image quality with head CT. In this study, we analyzed the improvement of image quality by proposed method to the noisy CT images. The proposed denoising method total variance optimization only for the impulsive noise candidate pixels. Experimental results show that edge information is well preserved and impulse noise can be effectively removed. and worked very well for the images according to tube voltage and rotation time. applied to the clinical setting, it can be used as the lowest exposure condition without worrying about the image quality and it will be helpful for the CT application.