• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.310-312
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• 2011

In complex noise environment, digital filter is being used to obtain, transport and storage original voice or image signal. Digital filter can be largely separated FIR(Finite duration impulse response) filter and IIR(Infinite duration impulse response) filter. Among FIR filter, window function has characteristic of linear phase and as can be easily set pass-band frequency, cutoff frequency and so on. In this paper, We compared with established method using transient characteristic and peak side-lobe in order to check filter characteristics after we designed the existing variants of the window function.

• 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.438-446
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• 2005

In this paper, the modified generalized Chebyshev rational function is presented. The new element values of prototype low pass filter are obtained by network synthesis using this rational function. This proposed filter has an equal ripple passband as same as conventional generalized Chebyshev filter, but unlike conventional filter which has only one attenuation pole at finite frequency, the proposed filter has two different from each other attenuation pole in stopband. If the harmonic frequency is set to the second attenuation pole frequency, this harmonic is suppressed efficiently. Furthermore, since the location of the second attenuation pole can be arbitrary adjusted. our filters are very available for the realization of wide stopband, particularly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.207-209
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• 2021

In recent years, with the development of artificial intelligence and IoT technology, automation and unmanned technology are in progress in various fields, and the importance of image processing such as object tracking, medical images and object recognition, which are the basis of this, is increasing. In particular, in systems requiring detailed data processing, noise reduction is used as a pre-processing step, but the existing algorithm has a disadvantage that blurring occurs in the filtering process. Therefore, in this paper, we propose a filter algorithm using modified spatial weights to minimize information loss in the filtering process. The proposed algorithm uses mask matching to remove AWGN, and obtains the output of the filter by adding or subtracting the output of the modified spatial weight. The proposed algorithm has superior noise reduction characteristics compared to the existing method and reconstructs the image while minimizing the blurring phenomenon.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.250-252
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated systems are progressing in various fields, and various application technologies are being studied in systems using algorithms such as object detection, recognition, and tracking. In the case of a system operating based on an image, noise removal is performed as a pre-processing process, and precise noise removal is sometimes required depending on the environment of the system. In this paper, we propose a modified central weight filter algorithm using pixel division of local regions to minimize the blurring that tends to occur in the filtering process and to emphasize the details of the resulting image. In the proposed algorithm, when a pixel of a local area is divided into two areas, the center of the dominant area among the divided areas is set as a criterion for the weight filter algorithm. The resulting image is calculated by convolving the transformed center weight with the pixel value inside the filtering mask.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.989-995
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• 2013

Image degradation caused by the impulse noise is generated in the process of image transmission and so on. It has been studied by many researchers in order to remove these noise. The representative impulse noise removal method includes SM filter. Though SM filter will indicate errors by the increasing of impulse noise density. Therefore, in this paper, in order to preserve the edges of the image, and reduce the distortion of the image, an improved adaptive median filter algorithm is proposed. In the simulation results, the algorithm showed excellent results in all several areas, and the PSNR is used as the criterion of evaluation.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.49-55
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• 2003

The use of digital filters in the signal process field is increasing rapidly with development of the modern industrial society. Especially, detail processors, Y/C separators, ghost removing filters, standard converters (NTSC to PAL or PAL to NTSC) and noise reducers, all of which use digital filters, tend to be used in digital video and audio processing, CATV and various communication fields. Generally, there are two different digital filters, the Rf (infinite impulse response) filter and the FIR (finite impulse response) filter in digital filter. In this paper, we have designed FIR filter which has the phase linearity and the easiness of creation. In the design of the FIR digital filter, the window function is used to alleviate the ripples caused by Gibbs Phenomenon around the cut off frequency of the band pass. But there're some problems to choose proper window function for the design destination due to its fixed values. Therefore, in this paper, we designed a modified Hanning window with new parameter which is adaptively chosen corresponding to design objectives. The digital filter was simulated to prove the validity of the model and it was compared with the Hamming, the Manning, the Blacknan and the Kaiser window function. And we have used peak side-lobe and transient characteristics as standard of judgement.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.1
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• pp.75-83
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• 2000

This paper deals with the application of two dimensional filtering technique for strain calculation using old and new geodetic data, and discusses the characteristics of general strain pattern in terms of seismic activity and tectonics. The mean rate of maximum shear strain is $0.12{\mu}/yr$. The mean direction of principal axes distribution of the compression is about $N80^{\circ}E$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.758-761
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• 2007

Digital signal processing technique is applied in wide fields such as speech processing, image processing and spectrum analysis. Therefore, in order to do frequency selective operation digital filter is used in stead of analog filter and sharp filter characteristics can be implemented. Since finite impulse response (FIR) digital filter as nonrecursive type represents linear phase response characteristics and is always stable and is used in fields regarding wave information importantly such as data transmission. And due to frequency characteristics, in order to remove the Gibbs phenomenon generating around a discontinuous point, filter is designed through window function method. Therefore, in this paper to improve performance of FIR digital filter, a modified window function was applied. And the proposed method was compared with conventional methods using peak side-lobe and transition properties in simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2447-2453
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• 2013

The digital images are being degraded by noise in the process of acquisition, storage and transmission, Gaussian or impulse noise is the representative noise. Meanwhile, the image has lots of tendency to be degraded by complex noise, so various researches are being conducted for reducing these complex noise. In this paper, to remove complex noise, the algorithm processed by modified switching median filter and modified adaptive weighted filter according to the result after judging the kinds of noise is proposed. In the simulation result, excellent denoising capabilities. Furthermore, we compared proposed algorithm with existing methods for objective judgement, and PSNR(peak signal to noise ratio) is used by the criterion of judgement.