• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.327-346
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• 2019

The goal of hyperspectral pansharpening is to combine a hyperspectral image (HSI) with a panchromatic image (PANI) derived from the same scene to obtain a single fused image. In this paper, a new hyperspectral pansharpening approach using adaptive weighted regression and guided filter is proposed. First, the intensity information (INT) of the HSI is obtained by the adaptive weighted regression algorithm. Especially, the optimization formula is solved to obtain the closed solution to reduce the calculation amount. Then, the proposed method proposes a new way to obtain the sufficient spatial information from the PANI and INT by guided filtering. Finally, the fused HSI is obtained by adding the extracted spatial information to the interpolated HSI. Experimental results demonstrate that the proposed approach achieves better property in preserving the spectral information as well as enhancing the spatial detail compared with other excellent approaches in visual interpretation and objective fusion metrics.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1234-1257
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• 2023

In this paper, we propose a framework for multi-focus image fusion called PATN. In our approach, by aggregating deep features extracted based on the U-type Transformer mechanism and shallow features extracted using the PSA module, we make PATN feed both long-range image texture information and focus on local detail information of the image. Meanwhile, the edge-preserving information value of the fused image is enhanced using a dense residual block containing the Sobel gradient operator, and three loss functions are introduced to retain more source image texture information. PATN is compared with 17 more advanced MFIF methods on three datasets to verify the effectiveness and robustness of PATN.

• Korean Security Journal
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• no.6
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• pp.167-193
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• 2003

Korean social structure is changing by leaps and bounds caused by industrialization, urbanization and information. Because of this, the sense of value, and moral consciousness of Korean people have been edteriorating and all kinds of social evils have been increasing also. However, the police who ought to be in charge of public well-being, security, social order are not playing their role on account of bad working conditions, and lack of budget. For this reason, individuals are desirous of preserving their security and lives at their cost. Private security has emerged at this background.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.53-56
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• 2001

This paper presents a computationally efficient post-processing algorithm for HDTV. The proposed algorithm can reduce both blocking artifacts and mosquito noise while preserving the sharpness and naturalness of the reconstructed video signal. Performance improvements compared with other techniques are obtained according to simulation results.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.381-384
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• 2001

본 논문에서는 경계영역을 잘 보존할 수 있는 움직임 추정기법을 제안하였다. 고정크기 블록으로 움직임 추정시 생길 수 있는 경계영역에서의 왜곡은 인간의 시각에 민감하게 작용할 수 있다. 제안한 움직임 추정기법은 고정크기 블록기반으로서 기본적으로 MAD(Mean Absolute Difference)가 최소가 되도록 하는 동시에 영상의 경계값과 복잡도를 이용하여 경계부분에서 일어나는 시각적인 왜곡을 줄일 수 있도록 하였다. 제안한 움직임 추정기법은 기존의 경계영역 보존 기법에 비해 직관적 성능 및 주관적 차질이 향상됨을 모의 실험결과로부터 확인하였다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.659-662
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• 2000

다양한 보간 기법을 정리해 보고 이를 통해서 기존의 보간 기법의 한계를 고찰해 본다. 보간의 효율성과 보간 결과 영상의 화질과는 Trade off 관계가 있으며, 이를 적절한 수준에서 결정하는 것은 중요한 문제이다. 본 논문에서는 Quadratic B-spline을 기저 함수로 하는 윤곽보존형 보간 필터를 사용한 영상확대 알고리즘을 제안한다. Unser의 Cardinal Cubic spline함수에 비해 적은 하드웨어만으로도 이상적인 저역 통과 필터의 특성을 가지며, 입력영상의 윤곽의 방향성을 고려한 적응적인 보간 기법의 적용으로 화질이 우수한 영상확대 알고리즘을 제안한다.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.2
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• pp.209-215
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• 2000

In this paper we present polyline upward order preserving grid drawing algorithm for binary trees with n vertices that achieves 0(n) height, 0(log n) width and 0(nlog n) area, matching the previously known results, and that reduces the number of bends to 0(n/log n) from 0(n)

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.131-138
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• 1998

We derive a back-propagation learning algorithm of fuzzy neural networks using fuzzy operations, which preserves the shapes of fuzzy numbers, in order to utilize fuzzy if-then rules as well as numerical data in the learning of neural networks for classification problems and for fuzzy control problems. By introducing the shape preseving fuzzy operation into a neural network, the proposed network simplifies fuzzy arithmetic operations of fuzzy numbers with exact result in learning the network. And we illustrate our approach by computer simulations on numerical examples.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.697-700
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• 1998

스테레오 영상으로부터 3차원 거리 정보를 추출하는 일은 수학적으로 불량 설정 문제(ill-posed problem)이다. 본 논문은 스테레오 정합을 정칙화(regularization)와 최소화(minimization) 문제로 설정하여 변이 (disparity)를 구한다. 최소화할 에너지 함수로 기울기 벡터(gradient vector)를 사용하여 촤우 카메라의 차이에 대응하고, 영상에 존재하는 깊이 불연속점(depth discontinuties)을 찾아내어 이를 보존하면서 정칙화를 실행하는 스테레오 정합 알고리즘을 제시한다. 다양한 스테레오 영상에 대한 실험 결과를 함께 나타내었다.