• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.289-291
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• 2016

본 논문에서는 VR의 발전과 함께 주목받고 있는 컴퓨터 비전 관련 기술들에 대하여 살펴보고, 가장 먼저 선행되어야 하는 이미지 필터링 알고리즘에 대하여 살펴 본다. 다양한 case에서의 여러 Image Filter를 구현, 성능을 비교 분석해 보고, 정확도를 향상 시킬 수 있는 방안에 대하여 연구한다.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2078-2080
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• 2001

본 논문은 기존의 가중 메디안 필터에 음의 가중치를 갖는 recursive weighted median(RWM) 필터 구조를 소개하고자 한다. 이는 연산과정에 퍼지 클러스터를 적용하여 또 다른 구조의 RWM 필터를 제안하였다. 제안된 RWM 필터는 infinte impulse response(IIR) 선형 필터의 부류로 상사되는 것으로서 기존의 선형 IIR 필터와는 달리 강건한 대역 또는 고역통과 필터의 특성 뿐만 아니라 피드백 되어진 계수 값에 상관없이 항상 BIBO 시스템에서의 안정성과 잡음에 강건한 특성을 나타낸다. 특히 퍼지 클러스터를 적용하여 중앙값 주변의 값을 적절히 취함으로서 신뢰성과 보다 빠른 연산속도의 성능을 여러 다른 구조의 필터들과 성능 비교 실험을 통해 입증하였다.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.175-182
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• 2017

Noises are usually generated by various external causes and low quality devices in image data acquisition and recording as well as by channel interference in image transmission. Since these noise signals result in the loss of information, subsequent image processing is subject to the corruption of the original image. In general, image processing is performed in the mixed noise environment where common types of noise, known to be Gaussian and impulse, are present. This study proposes an iterative weighted mean filter for reducing mixed type of noise. Impulse noise pixels are first turned off in the input image, then $3{\times}3$ sliding window regions are processed by replacing center pixel with the result of weighted mean mask operation. This filtering processes are iterated until all the impulse noise pixels are replaced. Applied to images corrupted by Gaussian noise with ${\sigma}=10$ and different levels of impulse noise, the proposed filtering method improved the PSNR by up to 12.98 dB, 1.97 dB, 1.97 dB respectively, compared to SAWF, AWMF, MMF when impulse noise desities are less than 60%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.89-96
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• 2009

In this paper, we propose an efficient deinterlacing algorithm which is an edge dependent interpolation based on edge direction refinement. The conventional edge dependent interpolation algorithms have a visually better performance than any other Intra-field deinterlacing algorithms. However they are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method detects edge direction of around interpolated pixel and refines the edge direction using weighted median filter. Simulation results have shown the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Journal of Biomedical Engineering Research
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• v.23 no.3
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• pp.253-261
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• 2002

A spatially adaptive falter was formulated to imrove PET image qualify and the Performance of the filter was evaluated using simulation and phantom and human PET studies. In the proposed filter. if a pixel was identified as the edge Pixel, the Pixel value was Preserved. Otherwise a Pixel was replaced by the mean of the pixel values weighted by 2:7: 2. A Pixel was identified as the edge Pixel. if it satisfies the following conditions : the number of ADs (absolute difference between center and neighborhood pixels) which is smaller than THl (($pix_max{\times}0.1/log_2(NPM)$, NPM : mean of 6 neighborhood pixels excluding minimum and maximum) is 8-k and the number of ADs which is lager than TH2 ($NPM{\times}0.1$) is k. where k : 2, 3, …, 6. The results of this study demonstrate the superior performance of the Proposed titter compared to Gaussian fitter, weight median filter and subset averaged median filter. The proposed tittering method is simple but effective in increasing uniformity and contrast with minimal degradation of spatial resolution of PET images and thus. is expected to Provide improved diagnositc quality PET images .