• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.218-224
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• 1998

The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

• Computers and Concrete
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• 제20권5호
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• pp.555-562
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• 2017

The accuracy and integrity of stress data acquired by bridge heath monitoring system is of significant importance for bridge safety assessment. However, the missing and abnormal data are inevitably existed in a realistic monitoring system. This paper presents a data reconstruction approach for bridge heath monitoring based on the wavelet multi-resolution analysis and support vector machine (SVM). The proposed method has been applied for data imputation based on the recorded data by the structural health monitoring (SHM) system instrumented on a prestressed concrete cable-stayed bridge. The effectiveness and accuracy of the proposed wavelet-based SVM prediction method is examined by comparing with the traditional autoregression moving average (ARMA) method and SVM prediction method without wavelet multi-resolution analysis in accordance with the prediction errors. The data reconstruction analysis based on 5-day and 1-day continuous stress history data with obvious preternatural signals is performed to examine the effect of sample size on the accuracy of data reconstruction. The results indicate that the proposed data reconstruction approach based on wavelet multi-resolution analysis and SVM is an effective tool for missing data imputation or preternatural signal replacement, which can serve as a solid foundation for the purpose of accurately evaluating the safety of bridge structures.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.648-650
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• 2003

Efficient multi-resolution image fusion aims to take advantage of the high spectral resolution of Landsat TM images and high spatial resolution of SPOT panchromatic images simultaneously. This paper presents a multi-resolution data fusion scheme, based on multirate image representation. Motivated by analytical results obtained from high-resolution multispectral image data analysis: the energy packing the spectral features are distributed in the lower frequency bands, and the spatial features, edges, are distributed in the higher frequency bands. This allows to spatially enhancing the multispectral images, by adding the high-resolution spatial features to them, by a multirate filtering procedure. The proposed method is compared with some conventional methods. Results show it preserves more spectral features with less spatial distortion.

• Spatial Information Research
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• 제10권2호
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• pp.331-343
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• 2002

최근 위성 영상정보를 이용하는 활용 연구의 중요성이 강조되면서 다중 분해능을 갖는 위성 영상정보의 통합적인 적용에 대한 관심이 증가하고 있다. 본 연구에서는 광역적인 분석에서 다중 분해능 위성 영상정보의 광역적 통합 분석에 대한 적용 가능성을 살펴보기 위하여 경기도 남양주시에 대한 Landsat 7 ETM+ 다중 분광 영상정보와 KOMPSAT EOC 영상정보에 대한 화소 값(DN) 분석 및 다중 분해능 영상 분류를 수행한 뒤에, 분류 결과를 같은 지역에 대하여 구축된 토지이용현황 주제도와 대비 분석하고자 하였다. 다중 분해능 영상 분류로 나타난 주요 결과로는 단일 분해능 영상정보 분류결과에 비하여 도로 정보와 같은 선형적인 요소의 추출이 용이한 것으로 나타났다. 한편 연구 지역내 주요 도로에 대한 영향권 설정 분석 또는 거리 질의 방법을 이용하여 수행된 영상 분류 결과와 토지이용현황 주제정보의 대비 분석 결과는 두 가지 정보가 유사한 패턴을 보이므로, 다중 분해능 영상정보의 분류 결과는 도시 환경분석문제에도 효과적으로 이용될 수 있을 것으로 생각된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.116-119
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• 2005

As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2006년도 전기학술대회논문집
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• pp.209-210
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• 2006

Digital technology has been applied to marine seismic survey to develop data processing technology and multi-channel marine seismic survey. In result, high-resolution marine seismic survey ended in a success. Surveys are conducted for various purposes using various frequencies of acoustic sources. A low frequency source is used for deeper penetration and a high frequency source is used for higher resolution survey. In this study, a multi-source system was used for multi-channel marine seismic survey to acquire seismic sections of both low and high frequencies. Variations of depth of penetration and resolution would be used to achieve more accurate analysis of formations. In this study, the multi-source system consists of Bubble Pulser(400 Hz) for low frequency source and Sparker(1.5 kHz) for high frequency source.

• Journal of Information Processing Systems
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• 제13권3호
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• pp.464-475
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• 2017

In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi-resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.

• 한국CDE학회논문집
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• 제7권2호
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• pp.121-130
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• 2002

The concept of Level Of Detail (LOD) was introduced and has been used to enhance display performance and to carry out certain engineering analysis effectively. We would like to use an adequate complexity level for each geometric model depending on specific engineering needs and purposes. Solid modeling systems are widely used in industry, and are applied to advanced applications such as virtual assembly. In addition, as the demand to share these engineering tasks through networks is emerging, the problem of building a solid model of an appropriate resolution to a given application becomes a matter of great necessity. However, current researches are mostly focused on triangular mesh models and various operators to reduce the number of triangles. So we are working on the multi-resolution of the solid model itself, rather than that of the triangular mesh model. In this paper, we propose multi-resolution representation of B-rep model by reordering and converting design features into an enclosing volume and subtractive features.

• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1467-1472
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• 2018

For the problem that the face image of surveillance video cannot be accurately identified due to the low resolution, this paper proposes a low resolution face recognition solution based on convolutional neural network model. Convolutional Neural Networks (CNN) model for multi-scale input The CNN model for multi-scale input is an improvement over the existing "two-step method" in which low-resolution images are up-sampled using a simple bi-cubic interpolation method. Then, the up sampled image and the high-resolution image are mixed as a model training sample. The CNN model learns the common feature space of the high- and low-resolution images, and then measures the feature similarity through the cosine distance. Finally, the recognition result is given. The experiments on the CMU PIE and Extended Yale B datasets show that the accuracy of the model is better than other comparison methods. Compared with the CMDA_BGE algorithm with the highest recognition rate, the accuracy rate is 2.5%~9.9%.

• 한국CDE학회논문집
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• 제10권6호
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• pp.444-454
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• 2005

Recently, the requirements of multi-resolution models of a solid model, which represent an object at multiple levels of feature detail, are increasing for engineering tasks such as analysis, network-based collaborative design, and virtual prototyping and manufacturing. The research on this area has focused on several topics: topological frameworks for representing multi-resolution solid models, criteria for the level of detail (LOD), and generation of valid models after rearrangement of features. As a solution to the feature rearrangement problem, the new concept of the effective zone of a feature is introduced in the former part of the paper. In this paper, we propose a feature-based non-manifold modeling system to provide multi-resolution models of a feature-based solid or non-manifold model on the basis of the effective feature zones. To facilitate the implementation, we introduce the class of the multi-resolution feature whose attributes contain all necessary information to build a multi-resolution solid model and extract LOD models from it. In addition, two methods are introduced to accelerate the extraction of LOD models from the multi-resolution modeling database: the one is using an NMT model, known as a merged set, to represent multi-resolution models, and the other is storing differences between adjacent LOD models to accelerate the transition to the other LOD. We also suggest the volume of the feature, regardless of feature type, as a criterion for the LOD. This criterion can be used in a wide range of applications, since there is no distinction between additive and subtractive features unlike the previous method.