• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.5
• /
• pp.55-62
• /
• 2000

In this paper, an algorithm for determining the optimal resolution has been described for measuring the actual length of circular objects. As the resolution gets higher, the measurement error in general becomes smaller because of the reduced distance per pixel. However, the higher resolution makes circular objects enlarged, which may produce an ill-conditioned system. That is, a small error in the boundary positions may result in a large error in the analysis of the circular objects. Taking this fact into account, a new measure is proposed to determine the optimal resolution. The actual errors have been calculated with various resolutions and the resolution with the minimum error has been decided as the optimal resolution. The analysis using various circles with different sizes indicates that the minimum measurement error is obtained when the whole circle appears in the screen as large as possible, regardless of the size of circle. The experimental results using real images have verified the validity of our analysis.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2002.08a
• /
• pp.856-859
• /
• 2002

A system for high-resolution analysis of defective elementary cell (R, G or B) on Flat Panel Display (FPD) is described. Based on multiple acquisitions of low-resolution shifted images of the display, our system doesn't require a high-resolution sensor neither tedious alignment of the display, and will remain up to date even facing an important increase of the display dimensions. Our process, highly automated and thus flexible and robust, is expected to perform a full analysis in less than 60s. It is mainly intended for production tests and display classification by manufacturers.

• Korean Journal of Remote Sensing
• /
• v.22 no.5
• /
• pp.337-350
• /
• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05b
• /
• pp.1179-1186
• /
• 2002

Macro scale distributed hydrological models simulate river discharge with better accuracy but it depends upon the grid resolution of input data. Effects of different input resolutions are studied here. Three different grid resolution input data obtained from HUBEX-IOP EEWB data and GAME Re-analysis data are used to simulate river discharge and compared against the observed one. CAME Re-analysis 1.25-degree resolution data are found quite satisfactory in larger basins, while HUBEX-IOP EEWB 10-minute resolution data are better for small catchments. GAME Re-analysis 2.5-degree resolution data did not give good result. Simulated results by using spatially interpolated data are rather worse than using original data. The Huaihe River basin $(132350\textrm{km}^2)$ is taken as the case of study.

• Journal of Korea Water Resources Association
• /
• v.56 no.10
• /
• pp.641-653
• /
• 2023

As climate change and urbanization are causing unprecedented natural disasters in urban areas, it is crucial to have urban flood predictions with high fidelity and accuracy. However, conventional physically- and deep learning-based urban flood modeling methods have limitations that require a lot of computer resources or data for high-resolution flooding analysis. In this study, we propose and implement a method for improving the spatial resolution of urban flood analysis using a deep learning based super-resolution technique. The proposed approach converts low-resolution flood maps by physically based modeling into the high-resolution using a super-resolution deep learning model trained by high-resolution modeling data. When applied to two cases of retrospective flood analysis at part of City of Portland, Oregon, U.S., the results of the 4-m resolution physical simulation were successfully converted into 1-m resolution flood maps through super-resolution. High structural similarity between the super-solution image and the high-resolution original was found. The results show promising image quality loss within an acceptable limit of 22.80 dB (PSNR) and 0.73 (SSIM). The proposed super-resolution method can provide efficient model training with a limited number of flood scenarios, significantly reducing data acquisition efforts and computational costs.

• Smart Structures and Systems
• /
• v.16 no.1
• /
• pp.47-65
• /
• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• Journal of the Korean Society of Safety
• /
• v.39 no.1
• /
• pp.70-81
• /
• 2024

With heavy rainfall due to extreme weather causing increasing damage, the importance of urban flood forecasting continues to grow. To forecast urban flooding accurately and promptly, a sewer network and surface grid with appropriate detail are necessary. However, for urban areas with complex storm sewer networks and terrain structures, high-resolution grids and detailed networks can significantly prolong the analysis. Therefore, determining an appropriate level of network simplification and a suitable surface grid resolution is essential to secure the golden time for urban flood forecasting. In this study, InfoWorks ICM, a software program capable of 1D-2D coupled simulation, was used to examine urban flood forecasting performance for storm sewer networks with various levels of simplification and different surface grid resolutions. The inundation depth, inundation area, and simulation time were analyzed for each simplification level. Based on the analysis, the simulation time was reduced by up to 65% upon simplifying the storm sewer networks and by up to 96% depending on the surface grid resolution; further, the inundation area was overestimated as the grid resolution increased. This study provides insights into optimizing the simplification level and surface grid resolution for storm sewer networks to ensure efficient and accurate urban flood forecasting.

• Structural Engineering and Mechanics
• /
• v.6 no.1
• /
• pp.115-124
• /
• 1998

A novel boundary stress resolution method is suggested in this paper, which is based upon the displacements of finite element analysis and of high precision with stress boundary condition strictly satisfied. The method is used to modify the Zienkiewicz-Zhu ($Z^2$) a posteriori error estimator and for the h-version adaptive finite element analysis of crack problems. Successful results are obtained.

• Korean Journal of Remote Sensing
• /
• v.40 no.1
• /
• pp.103-114
• /
• 2024

The escalating demands for high-resolution satellite imagery necessitate the dissemination of geospatial data with superior accuracy.Achieving precise positioning is imperative for mitigating geometric distortions inherent in high-resolution satellite imagery. However, maintaining sub-pixel level accuracy poses significant challenges within the current technological landscape. This research introduces an approach wherein upsampling is employed on both the satellite image and ground control points (GCPs) chip, facilitating the establishment of a high-resolution satellite image precision sensor orientation. The ensuing analysis entails a comprehensive comparison of matching performance. To evaluate the proposed methodology, the Compact Advanced Satellite 500-1 (CAS500-1), boasting a resolution of 0.5 m, serves as the high-resolution satellite image. Correspondingly, GCP chips with resolutions of 0.25 m and 0.5 m are utilized for the South Korean and North Korean regions, respectively. Results from the experiment reveal that concurrent upsampling of satellite imagery and GCP chips enhances matching performance by up to 50% in comparison to the original resolution. Furthermore, the position error only improved with 2x upsampling. However,with 3x upsampling, the position error tended to increase. This study affirms that meticulous upsampling of high-resolution satellite imagery and GCP chips can yield sub-pixel-level positioning accuracy, thereby advancing the state-of-the-art in the field.

• Computers and Concrete
• /
• v.20 no.5
• /
• pp.555-562
• /
• 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.