• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.26-31
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• 2012

The highest frequency band of wavelet decomposition band is divided into 4 equal subbands and by the minimum power of the subbands and by the monotonic transform, the level adapted threshold is obtained. The adapted threshold is applied to the soft threshold technique to denoise high and middle frequency band noise of image signals. And the results of PSNRs are compared with the results obtained by the VisuShrink technique and by the technique using the monotonic transform and the weight value. The results showed the validity of this technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.533-535
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• 2018

As the use frequency of electronic communication equipment increases due to the influence of the 4th industrial revolution, the importance of image and signal processing is increasing. However, due to noise caused by various causes, the reliability of the equipment is degraded and malfunctions are caused. In this paper, we propose an algorithm to remove AWGN in most environments. The existing methods show relatively poor performance due to the smoothing phenomenon at the boundary of the image. To overcome this problem, we proposed a filter algorithm that adapts to the boundary region using the Sobel edge detection to remove the noise. And using the PSNR compared with traditional methods, such as to demonstrate the performance of the proposed algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.29-34
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• 2002

In this paper, we present a new geometric active contour model based on level set methods introduced by Osher and Sethian for detection of object boundaries or shape and we adopt anisotropic diffusion filtering method for removing noise from original image. In order to minimize the processing time, we use the narrow band method which allows us to perform calculations in the neighborhood of the contour and not in the whole image. Using anisotropic diffusion filtering for each slice, we have the result with reduced noise and extracted exact shape. Volume rendering operates on three-dimensional data, processes it, and transforms it into a simple two-dimensional image.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.271-280
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• 2009

In this paper, we propose a smoke detection method using region growing method in outdoor video sequences. Our proposed method is composed of three steps; the initial change area detection step, the boundary finding and expanding step, and the smoke classification step. In the first step, we use a background subtraction to detect changed areas in the current input frame against the background image. In difference images of the background subtraction, we calculate a binary image using a threshold value and apply morphology operations to the binary image to remove noises. In the second step, we find boundaries of the changed areas using labeling algorithm and expand the boundaries to their neighbors using the region growing algorithm. In the final step, ellipses of the boundaries are estimated using moments. We classify whether the boundary is smoke by using the temporal information.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.45-52
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• 2000

In this study, we propose the image segmentation algorithm for facial region segmentation. The proposed algorithm separates the mean image of low frequency band from the differential image of high frequency band in order to make a boundary using HWT, and then we reduce the isolation pixels, projection pixels, and overlapped boundary pixels from the low frequency band. Also the boundaries are detected and simplified by the proposed boundary detection algorithm, which are cleared on the thinning process of 1 pixel unit. After extracting facial image boundary by using the proposed algorithm, we make the mask and segment facial image through matching original image. In the result of facial region segmentation experiment by using the proposed algorithm, the successive facial segmentation have 95.88% segmentation value.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.139-142
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• 1996

움직임 보상형 프레임간 내삽기법은 다른 동영상 압축기법과 함께 사용함으로써, 그 압축효과를 더욱 향상시킬 수 있는 장점을 가지고 있다. 그러나 블록에 기반한 기존의 움직임 보상형 프레임간 내삽기법을 움직이는 물체의 경계에서 심한 블록효과를 보인다. 본 논문에서는 Quad-tree 기법을 이용해 화소단위의 움직임을 추정하고, 이를 이용해 드러난 영역과 가리워지는 영역을 정확 히 예측해 보상함으로써 움직이는 물체의 경계에서 나타나는 블럭효과를 제거했다. 그리고 제안된 방법에서는 순방향이나 역방향 움직임추정 시 송신측으로 부터 보내지는 움직임 벡터를 이용함으로써 움직임 추정을 위해 소요되는 계산량을 최소화하였다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2203-2212
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• 1998

본 논문에서는 정규화 과정을 통해 2차원 물체를 인식하는 방법을 제안하고자 한다. 이를 위해 우선 입력 영상에 톨이론을 적용하여 화상구조를 파악함으로써 임계치 선정없이 잡음 제거와 경계 추출을 행한다. 그 후 추출된 경계선에 Hough 변환을 이용하여 직선과 원을 추출하여 여기에 프리미티브의 안정성에 기초하여 물체를 이루는 프리미티브에 대한 분리를 행한다. 최종적으로 분리된 프리미티브들로부터 모양 정도를 계산하고 디지털화 과정을 통해 인식 과정을 수행한다. 끝으로 본 논문의 유용성을 실험에 의해 입증하고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.505-513
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• 2004

Most video codecs including the international standards use the block-based hybrid structure for efficient compression. But for low bit-rate applications such as video transmission through wireless channels, the blocking artifacts degrade image qualify seriously. In this paper, we propose an adaptive de-blocking algorithm using characteristics of the block boundaries. Blocking artifacts contain the high frequency components near the block boundaries, therefore the lowpass filtering can remove them. However, simple lowpass filtering results into blurring by removing important information such as edges. To overcome this problem, we determine the modes depending upon the characteristics of pixels adjacent to block boundary then proper filter is applied to each area. Simulation results show that proposed method improves de-blocking performance compared to that of MPEG-4.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.2
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• pp.18-25
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• 2008

The current display systems including TVs are going digital and large-sized, and high visual quality of those systems becomes a very important selling point in the current display system market. Thus, various researches have been carried out for enhancing the visual quality of digital display systems. One of the important digital image(or video) enhancement techniques is sharpness enhancement, and it is generally based on a transient improvement technique that reduces the edge transition time. However, this technique often generates overshoot and undershoot, which cause undesirable pixel-level changes around the transient improved edge. In this paper, we propose a new nonlinear filter-based adaptive shoot elimination method for effectively suppressing the overshoot and undershoot that occur in the transient improvement, so that we can obtain visually sharper and clearer digital images(or videos). The proposed method uses two orthogonal directional min/max nonlinear filters with an adaptive shoot elimination scheme in order to effectively suppress the visually sensitive overshoot and undershoot. Experimental results show that the proposed method suppresses the overshoot and undershoot almost perfectly while maintaining the effect of the transient improvement. The applications of the proposed method include digital TVs, digital monitors, digital cameras/camcoders, portable media players(PMP), etc.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.344-349
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• 2009

동해의 SeaWiFS 클로로필-$\alpha$에서 나타나는 스펙클(speckle) 오차를 제거하고 Level-2에서 Level-3로의 자료합성을 실시하였다. 1998년부터 2007년까지 10년간 클로로필-$\alpha$의 시공간 변동성을 고려하여, 월 평균값으로 표준화된 공간적 표준 편차가 $7mg/m^3$ 이상 될 때를 경계 값으로 스펙클 제거기준을 설정하였다. 농도경사가 큰 전선지역과 연안으로부터 10-50 km 이내 지역은 제거 기준을 $12mg/m^3$ 이상으로 알고리즘을 구성하였다. 스펙클 제거 결과, 자료는 그대로 보존되고 스펙클이 존재하는 화소의 값만 줄어들었다. 특히 스펙클이 자주 발생하는 겨울철 클로로필 자료의 농도변화가 크게 나타났으며 스펙클이 많이 나타나는 시기에는 $5^{\circ}\times5^{\circ}$영역의 평균값이 10%이상 감소하는 결과를 보였다.