• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.24-24
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• 2015

최근 원격탐사기법을 이용한 많은 가뭄평가기법들이 개발되었으나 산림과 함께 산악지형이 우세한 우리나라의 경우 지형특성으로 인하여 가뭄평가시 불확실성이 증가하게 된다. 특히, 농업가뭄은 기후와 지표특성에 큰 영향을 받기 때문에 기후특성만을 고려한 가뭄지수는 실제 필요한 농업가뭄의 특성을 반영하는데 있어서 한계가 있다. 따라서 본 연구에서는 기후와 지표특성을 함께 고려할 수 있는 토양수분을 이용한 가뭄평가기법(Drought Assessment Scheme)을 개발하였다. 가뭄평가기법을 위하여 역추적기법(Inverse Modeling-IM) 기반의 자료동화기법(Data Assimilation, DA)을 이용하였다. 자료동화기법은 1-Dimensional (1-D) 기반의 토양의 물리적 특성을 고려하는 SWMI_ST 모형과 최적화 알고리즘(유전자 알고리즘, Genetic Algorithm-GA)을 연계하여 실측 및 위성기반의 토양수분자료로부터 토양의 수리학적 매개변수(${\alpha}$, n, ${\Theta}_{res}$, ${\Theta}_{sat}$, $K_{sat}$)를 추출한다. 본 연구에서는 LANDSAT(30 m X 30 m) 및 MODerate Resolution Imaging Spectroradiometer(MODIS, 500 m X 500 m) 이미지자료를 이용하여 시 공간적으로 분포되어 있는 토양수분을 산정하였으며, 이후 자료동화기법을 이용하여 LANDSAT/MODIS 토양수분자료로 부터 공간적으로 분포되어 있는 토양의 매개변수를 추출하였다. 추출된 매개변수, GIS 기반의 지표피복 및 기상자료를 이용하여 장기간의 토양수분을 산정 및 예측 할 수 있다. 고해상도의 이미지 자료를 사용하는 가뭄평가기법은 필지~시 군 단위까지 실제 우리나라 지형특성을 고려하여 효율적으로 가뭄을 모니터링 및 예측 할 수 있다.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.453-464
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• 2006

Web camera is usually used for video communication between PC, it has small sensing area, cannot using long exposure application, so that is insufficient for astronomical application. But web camera is suitable for bright planet, moon, it doesn't need long exposure time. So many amateur astronomer using web camera for planetary imaging. We used ToUcam manufactured by Phillips for planetary imaging and Registax commercial program for a video file combining. And then, we are measure a property of web camera, such as linearity, gain that is usually using for analysis of CCD performance. Because of using combine technic selected high quality image from video frame, this method on take higher resolution planetary imaging than one shot image by film, digital camera and CCD. We describe a planetary observing method and a video frame combine method.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.459-468
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• 2022

In medical area, very high resolution images, which is loss sensitive data, are used. Therefore, the use of optical internet with high bandwidth and the transmission of high realiability is required. However, according to the nature of the Internet, various data use the same bandwidth and a new scheme is needed to differentiate effectively these data. In order to achieve the differentiation, optical delay line buffers are used. However, these buffers is constructed based on some optimal values such as the average offered load, measured data burst length, and basic delay unit. Once the buffers are installed, they are impossible to reinstall new buffers. So, the scheme changing burst length dynamically was considered. However, this method is highly unstable. Therefore, in this article, in order to guarantee the stable operation of the scheme, the analysis of operation conditions is performed. With the analysis together with the scheme, high resolution medical data with the higher class can transmit stably without loss.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.417-417
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• 2023

도시홍수는 도시의 주요 기능을 마비시킬 수 있는 수재해로서, 최근 집중호우로 인해 홍수 및 침수 위험도가 증가하고 있다. 집중호우는 한정된 지역에 단시간 동안 집중적으로 폭우가 발생하는 현상을 의미하며, 도시 지역에서 강우 추정 및 예보를 위해 레이더의 활용이 증대되고 있다. 레이더는 수상체 또는 구름으로부터 반사되는 신호를 분석해서 강우량을 측정하는 장비이다. 기상청의 기상레이더(S밴드)의 주요 목적은 남한에 발생하는 기상현상 탐지 및 악기상 대비이다. 관측반경이 넓기에 도시 지역에 적합하지 않는 반면, X밴드 이중편파레이더는 높은 시공간 해상도를 갖는 관측자료를 제공하기에 도시 지역에 대한 강우 추정 및 예보의 정확도가 상대적으로 높다. 따라서, 본 연구에서는 딥러닝 기반 초해상화(Super Resolution) 기술을 활용하여 저해상도(Low Resolution. LR) 영상인 S밴드 레이더 자료로부터 고해상도(High Resolution, HR) 영상을 생성하는 기술을 개발하였다. 초해상도 연구는 Nearest Neighbor, Bicubic과 같은 간단한 보간법(interpolation)에서 시작하여, 최근 딥러닝 기반의 초해상화 알고리즘은 가장 일반화된 합성곱 신경망(CNN)을 통해 연구가 이루어지고 있다. X밴드 레이더 반사도 자료를 고해상도(HR), S밴드 레이더 반사도 자료를 저해상도(LR) 입력자료로 사용하여 초해상화 모형을 구성하였다. 2018~2020년에 발생한 서울시 호우 사례를 중심으로 데이터를 구축하였다. 구축된 데이터로부터 훈련된 초해상도 심층신경망 모형으로부터 저해상도 이미지를 고해상도로 변환한 결과를 PSNR(Peak Signal-to-noise Ratio), SSIM(Structural SIMilarity)와 같은 평가지표로 결과를 평가하였다. 본 연구를 통해 기존 방법들에 비해 높은 공간적 해상도를 갖는 레이더 자료를 생산할 수 있을 것으로 기대된다.

• Polymer(Korea)
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• v.32 no.1
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• pp.56-62
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• 2008

Three types of network polyesters have been newly synthesized by a two-step condensation reaction by the various combination of several diols and diacids. When these polymer films were thermally treated at $240^{\circ}C$, they exhibited absorptions in a visible range despite the forbidden transition of carbonyl group. When excited at wavelengths above 330 nm, the polymers showed fluorescences in a wide visible range from blue to near yellow. These fluorescence phenomena are due to the formation of certain conjugated structures by the Knoevenagel type self-condensation under the high-temperature thermal treatment. These polymers showed significant difference in the thermal properties as a function of the degrees of chemical crosslinking. They also underwent photodegradation. Highly resolved, fluorescent image patterns were successfully obtained by the photodegradation of malonate group under a strong UV-light irradiation.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.257-269
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• 2023

There is currently a burgeoning demand for image synthesis from photos and videos using deep learning models. Existing video synthesis models solely extract motion information from the provided video to generate animation effects on photos. However, these synthesis models encounter challenges in achieving accurate lip synchronization with the audio and maintaining the image quality of the synthesized output. To tackle these issues, this paper introduces a novel framework based on an image animation approach. Within this framework, upon receiving a photo, a video, and audio input, it produces an output that not only retains the unique characteristics of the individuals in the photo but also synchronizes their movements with the provided video, achieving lip synchronization with the audio. Furthermore, a super-resolution model is employed to enhance the quality and resolution of the synthesized output.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.11-20
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• 2024

Among the generative models in Artificial Intelligence (AI), especially Generative Adversarial Network (GAN) has been successful in various applications such as image processing, density estimation, and style transfer. While the GAN models including Conditional GAN (CGAN), CycleGAN, BigGAN, have been extended and improved, researchers face challenges in real-world applications in specific domains such as disaster simulation, healthcare, and urban planning due to data scarcity and unstable learning causing Image distortion. This paper proposes a new progressive learning methodology called Progressive Step Training (PST) based on the Auxiliary Classifier GAN (ACGAN) that discriminates class labels, leveraging the progressive learning approach of the Progressive Growing of GAN (PGGAN). The PST model achieves 70.82% faster stabilization, 51.3% lower standard deviation, stable convergence of loss values in the later high resolution stages, and a 94.6% faster loss reduction compared to conventional methods.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.153-165
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• 2010

Large-Scale Particle Image Velocimetry (LSPIV) is an extension of particle image velocimetry (PIV) for measurement of flows spanning large areas in laboratory or field conditions. LSPIV is composed of six elements - seeding, illumination, recording, image transformation, image processing, postprocessing - based on PIV. Possible error elements at each step of Mobile LSPIV (MLSPIV), which is a mobile version of LSPIV, in field applications are identified and summarized the effect of the errors which were quantified in the previous studies. The total number of elemental errors is 27, and five error sources were evaluated previously, seven elemental errors are not effective to the current MLSPIV system. Among 15 elemental errors, four errors - sampling time, image resolution, tracer, and wind - are investigated through an experiment at a laboratory to figure out how those errors affect to velocity calculation. The analysis to figure out the effect of the number of images used for image processing on the velocity calculation error shows that if over 50 images or more are used, the error due to it goes below 1 %. The effect of the image resolution on velocity calculation was investigated through various image resolution using digital camera. Low resolution image set made 3 % of velocity calculation error comparing with high resolution image set as a reference. For the effect of tracers and wind, the wind effect on tracer is decreasing remarkably with increasing the flume bulk velocity. To minimize the velocity evaluation error due to wind, tracers with high specific gravity is favorable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.233-235
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• 2011

Because of various style-sheet and Korean-Fonts, converting from WYSIWYG types of HTML data to forms of PDF has many limitations. In print-work areas, for printing specific fonts, it has to use CMYK colors instead of RGB colors. This paper describes about the process to make web font to printing PDF files, which is high resolution image captured document based on HTML, by using COM component feature of hardware.

• Journal of Korea Game Society
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• v.20 no.5
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• pp.13-20
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• 2020

Biometric technology with the advance of deep learning enabled the new types of content. Especially, face recognition can provide immersion in terms of convenience and non-compulsiveness, but most commercial content has limitations that are limited to application areas. In this paper, we attempted to overcome these limitations, implement content that can utilize face recognition technology based on realtime video feed. We used Unity engine for high quality graphics, but performance degradation and frame drop occurred. To solve them, we augmented Dlib toolkit and adjusted the resolution image.