• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.47-53
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• 2021

In this paper, we propose a quadtree-based optimization technique that enables fast Super-resolution(SR) computation by efficiently classifying and dividing physics-based simulation data required to calculate SR. The proposed method reduces the time required for quadtree computation by downscaling the smoke simulation data used as input data. By binarizing the density of the smoke in this process, a quadtree is constructed while mitigating the problem of numerical loss of density in the downscaling process. The data used for training is the COCO 2017 Dataset, and the artificial neural network uses a VGG19-based network. In order to prevent data loss when passing through the convolutional layer, similar to the residual method, the output value of the previous layer is added and learned. In the case of smoke, the proposed method achieved a speed improvement of about 15 to 18 times compared to the previous approach.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.133-143
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• 2010

This paper proposes a quadtree image compression method which encodes images efficiently and also makes unartificial compressed images. The proposed compression method uses edge-based quadtree decomposition to preserve the significant edge-lines, and it utilizes the predictive coding scheme to exploit the high correlation of the leaf node blocks. The simulation results with $256\times256$ grayscale images verify that the proposed method yields better coding efficiency than the JPEG by about 25 percents. The proposed method can provide more natural compressed images as it is free from the ringing effect in the compressed images which used to be in the images compressed by the fixed block based encoders such as the JPEG.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.99-106
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• 2007

In this paper, we present an AAW(Adaptive Attention Window) based cell image segmentation method. For semantic AAW detection we create an initial Attention Window by using a luminance map. Then the initial AW is reduced to the optimal size of the real ROI(Region of Interest) by using a quad tree segmentation. The purpose of AAW is to remove the background and to reduce the amount of processing time for segmenting ROIs. Experimental results show that the proposed method segments one or more ROIs efficiently and gives the similar segmentation result as compared with the human perception.

• Journal of Korea Game Society
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• v.7 no.1
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• pp.43-52
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• 2007

This article describes a new contribution culling method for fast rendering of complex huge urban scenes. A view frustum culling technique is used for fast rendering of complex scenes. To support the levels-of-detail, we subdivide the image regions and construct a weighted quadtree. Only visible objects at the current camera position contributes the current quadtree and the weight is assigned to each object in the quadtree. The weight is proportional to the image area of the projected object, so large buildings in the far distance are less likely to be culled out than small buildings in the near distance. The rendering time is nearly constant not depending on the number of visible objects. The proposed method has applied to a new metropolitan region which is currently under development. Experimental results showed that the rendering quality of the proposed method is barely distinguishable from the rendering quality of the original method, while the proposed method reduces the number of polygons by about 9%. Experimental results showed that the proposed rendering method is appropriate for real-time rendering applications of complex huge scenes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.361-364
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• 2012

MPEG과 ITU-T에서 최근 표준화가 진행되고 있는 HEVC는 H.264/AVC에 비해, CU(coding unit), PU(prediction unit), TU(transform unit)의 다양한 형태 분할 단위를 갖는 것을 큰 특징으로 한다. 이 중, CU와 TU는 쿼드트리 형태의 재귀적 분할 구조를 가지도록 구성되는데, 압축 효율은 향상시키지만 높은 부호화 복잡도를 갖는 단점이 있다. 본 논문에서는 이러한 재귀적 분할 구조를 변환하여 가장 작은 CU의 정보를 병합하여 큰 CU의 정보를 빠르게 결정하는 방법을 제안한다. 제안한 방법을 HEVC의 CU 부호화에 적용한 결과, 부호화 복잡도를 32-45% 가량 감소시키면서 압축 효율 하락은 0.6-0.9%로 억제할 수 있었다. 또한, HM6.1에 구현되어 있는 고속 탐색 알고리즘과 비교 할 경우, 압축 효율 하락을 0.2-0.3%로 억제하면서 부호화 복잡도를 8-12% 감소시킬 수 있었다.

• Journal of KIISE
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• v.45 no.3
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• pp.288-293
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• 2018

There have recently been several studies investigating how to apply a privacy preserving technique to publish data. Differential privacy can protect personal information regardless of an attacker's background knowledge by adding probabilistic noise to the original data. To perform differentially private k-means clustering, the existing algorithm builds a differentially private histogram and performs the k-means clustering. Since it constructs an equi-width histogram without considering the distribution of data, there are many buckets to which noise should be added. We propose a k-means clustering algorithm using a quad-tree that captures the distribution of data by using a small number of buckets. Our experiments show that the proposed algorithm shows better performance than the existing algorithm.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.63-66
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• 2009

본 논문에서는 트림영역이 있는 NURBS 평면을 등기하 해석할 수 있는 방법을 제시한다. 기존 등기하 해석법으로 트림 NURBS 곡면을 해석하기 위해서는 해석 도메인이 여러 개의 사각형 패치로 분할되어있어야 한다. 그러나 본 연구에서 제안한 방법은 CAD에서 제공하는 트림곡선의 정보를 해석에 직접 사용할 수 있기 때문에 CAD 모델을 별도로 재구성해야하는 번거로움이 없다. NURBS 곡선 투영법을 이용하여 트림되는 요소를 찾고, 트림된 요소는 쿼드트리 분할법과 NEFEM에서 사용된 적분방법을 동시에 고려하면 어떤 경우의 트림 요소라도 적분이 가능하다. 다양한 수치 예제를 통하여 제안한 해석 방법을 검증하고, 기존의 등기하해석법으로 해석하기 어려운 다수의 트림영역이 존재하는 NURBS 평면을 해석하여 본 방법의 유용성을 검토한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.194-196
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• 2014

HEVC(High Efficiency Video Coding)는 재귀적 쿼드트리 분할 구조의 부호화단위(CU: Coding Unit)와 각 CU에서 다양한 예측단위(PU: Prediction Unit)를 제공하고, 율-왜곡 기반으로 최적의 CU와 PU를 결정함으로써 높은 부호화 효율을 얻을 수 있는 반면 부호화 복잡도 또한 크게 증가하는 문제가 있다. 본 논문에서는 부호화기의 복잡도를 감소시키기 위해 상위깊이의 부호화 정보를 이용한 고속 부호화 기법을 제안한다. 제안기법은 상위깊이 CU의 Sub-CBF(coded block flag)를 이용하여 현재깊이 CU에서의 PU를 조기 결정하여 PU 탐색을 고속화 한다. 또한 화면내(Intra) 예측 고속화를 위하여 현재 CU의 sub-CBF를 함께 사용하여 하위깊이에서의 화면내 예측을 생략한다. 실험결과 제안기법은 HM 14.0 대비 1.2%의 BD-rate 증가에 31.4%의 부호화 시간 감소 효과를 얻을 수 있었다.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.105-113
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• 2019

Physically-based fluid simulation takes a lot of time for high resolution. To solve this problem, there are studies that make up the limitation of low resolution fluid simulation by using deep running. Among them, Super-resolution, which converts low-resolution simulation data to high resolution is under way. However, traditional techniques require to the entire space where there are no density data, so there are problems that are inefficient in terms of the full simulation speed and that cannot be computed with the lack of GPU memory as input resolution increases. In this paper, we propose a new method that divides and classifies 2D smoke simulation data into the space using the quad tree, one of the spatial partitioning methods, and performs Super-resolution only required space. This technique accelerates the simulation speed by computing only necessary space. It also processes the divided input data, which can solve GPU memory problems.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.162-165
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• 2020

본 논문에서는 차세대 비디오 압축 표준인 MPEG-5 Essential Video Coding (EVC) 에서 사용된 블록 분할 방식에 대해서 소개한다. EVC 에서 사용된 블록 분할 방식은 기존 비디오 압축 표준인 HEVC/H.265 에서 사용된 쿼드 트리(Quad-tree)가 아닌 이진 분할(Binary split)과 삼진 분할(Ternary split)을 사용한 Binary ternary tree(BTT) 기술을 사용하고 있다. 또한 기존 비디오 압축 기술과 달리 분할된 블록의 코딩 순서를 정해서 사용 할 수 있는 Split unit coding order (SUCO) 기술이 사용되고 있다.