• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.12-18
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• 2006

This paper presents a method to extract a good high-resolution image from a low-resolution video in an automatic manner. Since a high-resolution image reconstruction method utilizing several low-resolution input images works better than a conventional interpolation method utilizing single low-resolution input image only if the input images are well registered onto a common high-resolution grid, low-resolution input images should be carefully chosen so that the registration errors can be carefully considered. In this paper, the statistics obtained from the motion-compensated low-resolution images are utilized to evaluate the feasibility of the input image candidates. Maximum motion-compensation error is estimated from the high-resolution image observation model. U the motion-compensation error of the input image candidate is greater than the estimated maximum motion-compensation error, the input image candidate is discarded. The number of good input image candidates and the statistics of the motion-compensation errors are used to choose final input images. The final input images chosen from the input image selection block are given to the following high-resolution image reconstruction block. It is expected that the proposed method is utilized to extract a good high-resolution image efficiently from a low-resolution video without any user intervention.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.1-6
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• 2024

Recently, various techniques are being applied through the development of medical AI, and research has been conducted on the application of super-resolution AI models. In this study, evaluate the results of the application of the super-resolution AI model to brain CT as the basic data for future research. Acquiring CT images of the brain, algorithm for brain and bone windowing setting, and the resolution was downscaled to 5 types resolution image based on the original resolution image, and then upscaled to resolution to create an LR image and used for network input with the original imaging. The SRCNN model was applied to each of these images and analyzed using PSNR, SSIM, Loss. As a result of quantitative index analysis, the results were the best at 256×256, the brain and bone window setting PSNR were the same at 33.72, 35.2, and SSIM at 0.98 respectively, and the loss was 0.0004 and 0.0003, respectively, showing relatively excellent performance in the bone window setting CT image. The possibility of future studies aimed image quality and exposure dose is confirmed, and additional studies that need to be verified are also presented, which can be used as basic data for the above studies.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.1-8
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• 2018

This paper proposes a low complexity super resolution algorithm for frequency modulated continuous wave (FMCW) radar systems for foreign object debris (FOD) detection. FOD radar has a requirement to detect foreign object in small units in a large area. However, The fast Fourier transform (FFT) method, which is most widely used in FMCW radar, has a disadvantage in that it can not distinguish between adjacent targets. Super resolution algorithms have a significantly higher resolution compared with the detection algorithm based on FFT. However, in the case of the large number of samples, the computational complexity of the super resolution algorithms is drastically high and thus super resolution algorithms are difficult to apply to real time systems. In order to overcome this disadvantage of super resolution algorithm, first, the proposed algorithm coarsely obtains the frequency of the beat signal by employing FFT. Instead of using all the samples of the beat signal, the number of samples is adjusted according to the frequency of the beat signal. By doing so, the proposed algorithm significantly reduces the computational complexity of multiple signal classifier (MUSIC) algorithm. Simulation results show that the proposed method achieves accurate location even though it has considerably lower complexity than the conventional super resolution algorithms.

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

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.178-185
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• 2021

Three-dimensional high-resolution magnetic resonance imaging (MRI) provides fine-level anatomical information for disease diagnosis. However, there is a limitation in obtaining high resolution due to the long scan time for wide spatial coverage. Therefore, in order to obtain a clear high-resolution(HR) image in a wide spatial coverage, a super-resolution technology that converts a low-resolution(LR) MRI image into a high-resolution is required. In this paper, we propose a super-resolution technique through filter learning based on information on the surrounding gradient information in 3D space from 3D MRI images. In the learning step, the gradient features of each voxel are computed through eigen-decomposition from 3D patch. Based on these features, we get the learned filters that minimize the difference of intensity between pairs of LR and HR images for similar features. In test step, the gradient feature of the patch is obtained for each voxel, and the filter is applied by selecting a filter corresponding to the feature closest to it. As a result of learning 100 T1 brain MRI images of HCP which is publicly opened, we showed that the performance improved by up to about 11% compared to the traditional interpolation method.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.6
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• pp.793-805
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• 2012

This study investigated the influence of mother and peer attachment on conflict resolution strategies of children. Following research questions were established. First, what is the influence of mother and peer attachment on conflict resolution strategies of children? Second, does the influence of mother and peer attachment on conflict resolution strategies of children differ according to sex? Third, what is the relative influence of mother and peer attachment on conflict resolution strategies of children? 485 fifth graders(male, 184; female, 163) from elementary schools located in Busan participated in this study and completed Inventory of Parent and Peer Attachment and Conflict Resolution Strategies Scale. Collected data were analyzed using t-test, Pearson Correlation Coefficient, Simple Regression and Multiple Regression Analysis. Major findings of this study were summarized as follows: First, both mother and peer attachment influenced on compromising and integration, avoiding and obliging strategies although the degree of influence were different. Second, the influence of mother and peer attachment on conflict resolution strategies differ according to gender. Third, the influence of peer attachment on conflict resolution strategies were greater than the one of mother attachment. Finally the significance of this study were presented with comments on limitations of this study.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.417-425
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• 2020

Multi-resolution modeling(MRM) is required when simulating objects in variable resolution and can be applied for interoperating systems, which simulate objects in fixed resolution. However, most interoperation middleware do not support MRM, so participating models must handle several issues to simulate MRM system. In this paper, we propose an interoperation system, which is composed of several different resolution models, based on the High Level Architecture and Run-Time Infrastructure(HLA/RTI). In the proposed architecture, each model participates to a HLA federation through MRM adapter application, which supports data resolution conversion and HLA services while communicating with the model. MRM adapter application can be implemented based on an MRM adapter, and an adapter application development tool is proposed to support developing the application. Using the tool, developers can easily implement data resolution conversion component plugged-in HLA adapter. A case study is implemented in the proposed MRM system, and shows that models of different resolution works successfully with dynamic resolution changes.

• Korean Journal of Digital Imaging in Medicine
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• v.13 no.4
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• pp.145-151
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• 2011

The purpose of this study is to know some changes of resolution and image if we remove scattered ray using lead plate when doing lumbar lateral projection. Using 3 DR system(2 FD types, 1 CCD type) equipments and 2 film system equipments, we gain the image whether the phantom of abdomen equivalent sticking resolution chart has lead plate or not, whether we do collimation or not. Also, we use ion chamber, measure radiation exposure rate and change to entrance surface dose from it. we gain that images in the greatest condition of taking in clinic. 5 people in this group decoded resolution with our eyes, measured thickness of images and compared them from each equiments. Resolution has difference to size of collimation in DR FD type. Also there is no difference the original image with the new image which we abbreviated mAs. In DR CCD type, resolution didn't have difference whether lead plate is or not and whether we do collimation or not. In film type, existing or nonexisting of lead plate didn't influence on resolution. Lead plate makes the quality of image higher due to reducing scattered ray, it doesn't influence on resolution.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.865-876
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• 2018

This study focuses on the operating requirements of multi-resolution modeling(MRM) in training war-game model and proposes solutions for major issues of multi-resolution interoperation between Combat21 model and tank multi-purpose simulator(TMPS). We study the operating requirements of MRM through interviews with defense M&S experts and literature surveys and report the various issues that could occur with low-resolution model Combat21 and high-resolution model TMPS linked, for example, when to switch objects, what information to exchange, what format to switch to, and how to match data resolutions. This study also addresses the purpose and concept of training using multi-resolution interoperation, role of each model included in multi-resolution interoperation, and issue of matching damage assessments when interoperated between models with different resolutions. This study will provide the common goals and directions of MRM research to MRM researchers, defense modeling & simulation organizations and practitioners.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.72-79
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• 2007

In this paper, It propose a new restoration algorithm of high resolution, which is reconstructed to high resolution image using low resolution image informations. The proposed algorithm is constructed based on super resolution theory, it is consisted of progressive steps of the integration and construction. It reduced a lot of data-processing capacity and noise with integration through sub-pixel movement and wavelet basis through a higher resolution. As a result, it is shown that the main information is maintained and the error rate is improved. Using expansion fuzzy wavelet B-spline interpolation in stage of construction, it is confirmed that we can achieve smoothing image and good resolution without blur and block.