• Journal of the Korean Geophysical Society
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• v.2 no.2
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• pp.143-152
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• 1999

We have studied a denoising technique involving wavelet transform for improving the quality of geophysical data during the preprocessing stage. To assess the effectiveness of this technique, we have made synthetic data contaminated by random noises and compared the results of denoising with those obtained by conventional low-pass filtering. The low-pass filtering of the sinusoidal signal having a sharp discontinuity between the first and last sample values shows apparent errors related to Gibbs' phenomena. For the case of bump signal, the low-pass filtering induces maximum errors on peak values by removing some high-frequency components of signal itself. The wavelet transform technique, however, denoises these signals with much less adverse effects owing to its pertinent properties on locality of wavelet and easy discrimination of noise and signal in the wavelet domain. The field data of gravity tide are denoised by using soft threshold, which shrinked all the wavelet coefficients toward the origin, and the G-factor is determined by comparing the denoised data and theoretical data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.477-481
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• 2009

In this paper the process of transmitting images signal restore to image corrupted by impulse noise proposed switching mean filter. these filter is differential size using the two state noise detection distinguishes noise pixel and noise free pixel. Follow the detected impulse noise density in the image remove the impulse noise using switching mean filter these substituted pixel in order to non-recursive and recursive form from control process of the next pixel comes to be used with neighbor pixel process. Through the simulation, we compared with the existing methods and capabilties.

• Annual Conference of KIPS
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• 2010.04a
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• pp.447-450
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• 2010

하모닉 초음파 영상은 일반 초음파 영상에 비해 조직 간의 영상 대조도와 해상도를 향상 시키고, 경계가 보다 명확하기 때문에 초음파 영상 진단 분야에서 각광받고 있다. 하지만 초음파 영상이 포함하고 있는 스펙클 잡음 (speckle noise)에 의한 화질 저하는 하모닉 초음파 영상에서도 여전히 문제가 되고 있다. 이러한 스펙클 잡음을 제거하기 위해 많은 스펙클 제거 (despeckling) 방법들이 연구되었으며, 대부분의 방법들이 영상의 시각적 개선에 초점을 두고 있다. 이러한 접근 방법은 잡음개선정도와 영상의 정보 손실의 상반 관계 (trade off)를 갖는다. 한편 병변 분할은 이런 잡음 제거 방법에 따라 다른 분할 성능을 보이게 된다. 따라서 정확한 병변 분할을 위해서는, 스펙클 제거 방법에 따른 병변 분할 성능을 비교하고, 그 결과를 토대로 병변 분할에 효과적인 스펙클 제거 방법에 대한 연구가 필요하다. 본 논문에서는 유방 하모닉 초음파 영상에서 다양한 스펙클 제거 방법을 사용하여 각각의 필터가 병변 분할 성능에 미치는 영향을 비교해 보았으며, 실험 결과를 바탕으로 유방 병변 분할에 효과적인 전처리 역할을 수행하는 필터에 대해 분석해 보았다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.666-668
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• 2016

Salt and pepper noise generally occurs due to errors in the transmission channel or sensors and it lowers the resolution of the image and causes visual errors. To remove this salt and pepper noise, SMF(standard median filter), which represents simple algorithm and excellent noise removal performance, is widely used. However preservation characteristics in the pitch areas of the image is rather lacking. Therefore to effectively restore images damaged by salt and pepper noise, the study suggested a multiple filter that applies filters differently according to size by applying noise density threshold value of local mask on noise signal, while preserving non-noise signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.793-796
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• 2017

Image signal can be damaged by a variety of noises during the signal processing, and multiple studies have been conducted to restore these signals. The representative noises to be added in the image are salt and pepper noise, additive white Gaussian noise(AWGN), and the composite noise which two noises are combined. Therefore, the algorithms were proposed to process with quadratic spline interpolation and median filter in case of salt and pepper noise with the central pixel of the local mask, and to process with weight filter by pixel changes in case of AWGN, upon noise determination to restore the damaged image in the composite noise environment, in this article.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.43-48
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• 2011

Among various methods proposed earlier, fuzzy image filtering is usually one of the favored techniques because it has less blurring effect and the decrease of noise removal rate after filtering. However, fuzzy filtering is ineffective on color images since it is firstly developed with gray scale. Thus, in this paper, we propose a fuzzy filtering algorithm for color images. First, we divide RGB color information from image into three channels of R, G, and B and judge the possibility of each pixel with mask by fuzzy logic independently. The output pixel value might be the average or median according to the degree of noise. Our experiment successfully verifies the effectiveness of new algorithm in color image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.213-215
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• 2021

With the development of IoT technology, various technologies such as artificial intelligence and automation are being grafted into industrial sites, and accordingly, the importance of data processing is increasing. In particular, a system based on a digital image may cause a malfunction due to noise in the image due to a sensor defect or a communication environment problem. Therefore, research on image processing has been continued as a pre-processing process, and an effective noise reduction technique is required depending on the type of noise and the characteristics of the image. In this paper, we propose a modified spatial weight filter to protect edge components in the impulse noise reduction process. The proposed algorithm divides the filtering mask into four regions and calculates the standard deviation of each region. The final output was filtered by applying a spatial weight to the region with the lowest standard deviation value. Simulation was conducted to evaluate the performance of the proposed algorithm, and it showed superior impulse noise reduction performance compared to the existing method.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.137-144
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• 2004

ECG signals are often contaminated with high-frequency noise such as muscle artifact, power line interference, and others. In the ECG signal processing, especially during a pre-processing stage, numerous noise removal techniques have been used to reduce these high-frequency noise without much distorting the original signal. This paper proposes a new type of digital filter with a continuously variable cutoff frequency to improve the signal quality This filter consists of a cutoff frequency controller (CFC) and variable cutoff frequency lowpass filter (VCF-LPF). From the noisy input ECG signal, CFC produces a cutoff frequency control signal using the signal slew rate. We implemented VCF-LPF based on two new filter design methods called convex combination filter (CCF) and weight interpolation fille. (WIF). These two methods allow us to change the cutoff frequency of a lowpass filter In an arbitrary fine step. VCF-LPF shows an excellent noise reduction capability for the entire time segment of ECG excluding the rising and falling edge of a very sharp QRS complex. We found VCF-LPF very useful and practical for better signal visualization and probably for better ECG interpretation. We expect this new digital filter will find its applications especially in a home health management system where the measured ECG signals are easily contaminated with high-frequency noises .

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.503-505
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• 1999

경계선 검출은 컴퓨터를 이용한 영상인식의 첫 단계로서, 인식의 성능에 큰 영향을 미치는 중요한 기술이다. 여러 가지 경계선 검출 기술들이 존재하지만, 이들은 모두 주어진 영사에 잡음이 존재하지 않거나 존재의 정도가 미약한 경우를 가정하여 개발되었다. 한편, 잡음이 심하게 삽입된 경우에는 경계선 검출기 적용 이전에 잡음제거 필터를 사용할 수 있다. 그러나 주어진 영상에 잡음이 존재하는지를 어떻게 컴퓨터 스스로 판단할 것인가\ulcorner 본 연구에서는 주어진 영상에 대하여 잡음의 존재 여부와 잡음의 정도 여부에 상관없이, 굳건한 경계선 검출 능력을 보이는 경계선 검출기를 개발하였다. 이를 위하여 이중 필터를 사용하였는데, 그 중 하나는 일반적으로 많이 사용되는 가우시안 필터이고, 다른 하나는 본 연구진에 의하여 개발된 웨이블릿 기반 필터이다. 실험결과, 본 논문의 경계선 검출기는 잡음의 정도에 크게 구애받지 않는 일정한 성능을 보여주었다.