• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.229-232
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• 1996

본 논문에서는 공간적 보간을 응용하여 손상된 영상 구획의 데이터를 복원하는 기법을 제시한다. 이러한 기법은 손상된 영상을 부가 정보 없이 복원하는 오류 은폐의 핵심으로 Park[3], Wang[4], Sun[9], Lee[7], Hemami[8] 등에 의해서 여러 가지 기법들이 제안되었다. 그러나 이러한 기법들은 단순히 주변 구획과의 경계면에서의 연속성만을 고려하여 복원하므로 구획 내부의 데이터를 복원하는데 한계가 있으며 계산량도 많은 단점이 있다. 따라서 본 논문에서는 이러한 기존의 기법들의 단점을 극복하기 위하여 Non-Unform Rational B-Spline(NURBS)을 응용한 복원 기법을 제안한다. 제시된 주변 구획의 오류 유무와 윤곽선의 방향에 따라 주변 구획의 화소 정보에 할당되는 가중치를 적절히 변경하여 NURBS를 적용한다. 따라서 윤곽선의 방향을 더욱 견실하게 복원함으로써 주관적, 객관적 관점에서 기존의 기법보다 우수한 영상 구획 복원 성능을 얻을 수 있다. 정지 영상에 대한 컴퓨터 모의 실험 결과 제안하는 알고리듬을 기존의 기법보다 30% 구획 손실율에서 0.5 dB이상 성능 향상을 얻을 수 있음을 관찰하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1672-1686
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• 2013

In this paper, we propose a hybrid super-resolution algorithm robust to cut-change. Existing single-frame based super-resolution algorithms are usually fast, but quantity of information for interpolation is limited. Although the existing multi-frame based super-resolution algorithms generally robust to this problem, the performance of algorithm strongly depends on motions of input video. Furthemore at boundary of cut, applying of the algorithm is limited. In the proposed method, we detect a define boundary of cut using cut-detection algorithm. Then we adaptively apply a single-frame based super-resolution method to detected cut. Additionally, we propose algorithms of normalizing motion vector and analyzing pattern of edge to solve various problems of existing super-resolution algorithms. The experimental results show that the proposed algorithm has better performance than other conventional interpolation methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.927-929
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• 2011

Since DVC (Distributed Video Coding) and FRUC (Frame Rate Up Conversion) techniques need to have an efficient motion compensated frame interpolation algorithms. Conventional works of these applications have mainly focused on the performance improvement of overall system. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame matches the original frame. For this aim, this paper deals with the modeling methods for evaluating the block-based matching cost. First, several matching criteria, which have already been dealt with the motion compensated frame interpolation, are introduced and then combined to make estimate models for the size of MSE (Mean Square Error) noise of the MCI frame to original one. Through computer simulations, it is shown that the block-based cost evaluation models are tested and can be effectively used for estimating the MSE noise.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.63-73
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• 2015

In this paper, a quality improvement scheme is proposed for magnified image using the various curved surface characteristics of image. After testing horizontal and vertical directional surface characteristics of source image, interpolation value is calculated to have the surface characteristics such as simple convex surface, simple concave surface, and compound surface. The calculated interpolation value become the value of the interpolated pixel of magnified image. The calculated interpolation value is closer to the pixel value of real image. So, the quality of the magnified image is improved. The PSNR value of the magnified image using the proposed scheme is larger than the PSNR values of the magnified image using the existing techniques.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.18-26
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• 2009

Image resolution enhancement algorithm is a basic technique for image enlargement and restoration. The main problem is the image quality degradation such as blurring or blocking effects. In this paper, we propose loss information estimation and image resolution enhancement method using low level interpolation method. In the proposed method, loss information is computed by downsampling -interpolation process of obtained low resolution image. We estimate loss information of high resolution image using interpolation of the computed loss information. Lastly, we add up interpolated high resolution image and the estimated loss information which is applied a weight factor. Our experiments obtained the average PSNR 1.4dB which is improved results better than conventional algorithm. Also subjective image quality is more clearness and distinctness. The proposed method may be helpful for various video applications which required improvement of image.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.238-246
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• 2005

This paper proposes an iterative high-resolution image interpolation algorithm using spatially adaptive constraints and regularization functional. The proposed algorithm adapts adaptive constraints according to the direction of..edges in an image, and can restore high-resolution image by optimizing regularization functional at each iteration, which is suitable for edge directional regularization. The proposed algorithm outperforms the conventional adaptive interpolation methods as well as non-adaptive ones, which not only can restore high frequency components, but also effectively reduce undesirable effects such as noise. Finally, in order to evaluate the performance of the proposed algorithm, various experiments are performed so that the proposed algorithm can provide good results in the sense of subjective and objective views.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.77-80
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• 2006

본 논문에서는 블록 기반의 영상압축에 있어서 선택적 방향성 보간을 이용하는 공간적 에러 은닉 기법을 제안한다. 기존의 공간적 경계 정합 기법은 에지가 단순한 영역에서는 좋은 성능을 보이지만, 손실 블록 내에서 에지의 변화가 큰 영역에서는 좋지 못한 성능을 보인다. 제안된 기법은 이웃한 상하 블록들을 이용하여 에지의 연결성을 추정하고, 이에 따라 공간적 경계정합 기법과 이동 스트라이프 정합 기법을 선택적으로 이용한다. 따라서 에지변화에 적응적으로 대응함으로써 우수한 복원영상을 구할 수 있다. 제안된 기법은 슬라이스 단위의 에러에 대해 적합한 방식으로써, 복잡도가 낮을 뿐만 아니라 객관적 주관적으로 우수한 복원 화질을 얻게 해준다.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.192-207
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• 2020

We acquire seismic data with regularly or irregularly missing traces, due to economic, environmental, and mechanical problems. Since these missing data adversely affect the results of seismic data processing and analysis, we need to reconstruct the missing data before subsequent processing. However, there are economic and temporal burdens to conducting further exploration and reconstructing missing parts. Many researchers have been studying interpolation methods to accurately reconstruct missing data. Recently, various machine learning technologies such as support vector regression, autoencoder, U-Net, ResNet, and generative adversarial network (GAN) have been applied in seismic data interpolation. In this study, by reviewing these studies, we found that not only neural network models, but also support vector regression models that have relatively simple structures can interpolate missing parts of seismic data effectively. We expect that future research can improve the interpolation performance of these machine learning models by using open-source field data, data augmentation, transfer learning, and regularization based on conventional interpolation technologies.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.4 s.74
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• pp.429-440
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• 2006

This paper comprises two specific objectives. The first is to examine the applicability of ordinary kriging interpolation(OK) to the p-adaptivity of the finite element method that is based on variogram modeling. The second objective Is to present the adaptive procedure by the hierarchical p-refinement in conjunction with a posteriori error estimator using the modified S.P.R. (superconvergent patch recovery) method. The ordinary kriging method that is one of weighted interpolation techniques is applied to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by experimental and theoretical variograms for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In the p-refinement, the analytical domain has to be refined automatically to obtain an acceptable level of accuracy by increasing the p-level non-uniformly or selectively. To verify the performance of the modified S.P.R. method, the new error estimator based on limit value has been proposed. The validity of the proposed approach has been tested with the help of some benchmark problems of linear elastic fracture mechanics such as a centrally cracked panel, a single edged crack, and a double edged crack.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.122-124
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• 2014

보간 기법은 영상의 해상도를 변경하는 것이다. 멀티미디어 기기의 해상도가 다양하기 때문에 원 영상은 각각에 맞는 해상도로 변경되어야 한다. 해상도 변경은 존재하지 않는 값을 임의로 만들어 채우는 것이기 때문에 왜곡이 발생한다. 대부분의 scaler에서는 수평과 수직 방향으로 해상도 변경을 하는데, 이 때문에 edge 영역에서는 왜곡이 더 많이 발생하며 쉽게 눈에 띈다. 본 논문에서는 edge 방향에서 발생하는 왜곡을 극복하기 위해 영상의 edge 정보와 Cubic Convolution을 이용해 임의의 배율로 해상도를 변경하는 방법을 제안한다.