• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.413-413
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• 2000

In this paper, we propose a series of calibrations f3r the x-ray three dimensional imaging system. In the developed x-ray system, a three dimensional inner and outer shape of an object can be reconstructed out of two dimensional transmitted x-ray image set, which are acquired by projecting x-ray to the object from different views. To achieve this, a reconstruction algorithm which estimates and updates the three dimensional volume from x-ray images is developed. The algorithm is named as uniform and simultaneous algebraic reconstruction technique(USART) which is an iterative method estimating a 3D volume based on its projected images. In this method, it is assumed that the imaging conditions that are the relative positions between the x-ray sources, object and the image planes are blown. Practically it is not easy to know the three dimensional coordinate of the components of the system, since the x-ray is not visible and the image distortions are present due to the optical components in the system. In this paper, methods of correcting image distortions are present firstly. Then the coordinates of the x-ray systems are calibrated from the x-ray images of the grid pattern. Some experimental results on these calibrations are present and discussed.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.141-146
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• 2002

Chlorophyll-a concentration maps of Yongdam reservoir in September and October, 2001 were produced using Landsat ETM imagery and the in-situ water quality measurement data. In-situ water samples were collected on 16th September and 18th October during the satellite overpass. The correlations between the DN values of the imagery and the values of chlorophyll-a concentration were analyzed. The visible bands(band 1, 2, 3) and the near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed correlation coefficient values of about 0.7 due to the low variations of chlorophyll-a concentration. Regression models between the DN values of the Landsat ETM image and the chlorophyll-a concentration have been developed for each image. The developed regression models were then applied to each image, and finally the chlorophyll-a distribution maps of Yongdam reservoir were produced. The produced maps showed the spatial distribution of the chlorophyll-a in Yongdam reservoir in a synoptic way so that the tropic state could be easily monitored and analysed in the spatial domain.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.111-116
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• 2021

The hyper-spectral image is data obtained by dividing the electromagnetic wave band in the infrared region into hundreds of wavelengths. It is used to find or classify objects in various fields. Recently, deep learning classification method has been attracting attention. In order to use hyper-spectral image data as deep learning training data, a processing technique is required compared to conventional visible light image data. To solve this problem, we developed a software that selects specific wavelength images from the hyper-spectral data cube and performs the ground truth task. We also developed software to manage data including environmental information. This paper describes the configuration and function of the software.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.49-59
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• 2019

Generative adversarial networks(GANs) have received great attention in the machine learning field for their capacity to model high-dimensional and complex data distribution implicitly and generate new data samples from the model distribution. This paper investigates the model training methodology, architecture, and various applications of generative adversarial networks. Experimental evaluation is also conducted for generating synthetic image dataset for defense using two types of GANs. The first one is for military image generation utilizing the deep convolutional generative adversarial networks(DCGAN). The other is for visible-to-infrared image translation utilizing the cycle-consistent generative adversarial networks(CycleGAN). Each model can yield a great diversity of high-fidelity synthetic images compared to training ones. This result opens up the possibility of using inexpensive synthetic images for training neural networks while avoiding the enormous expense of collecting large amounts of hand-annotated real dataset.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.82-86
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• 2017

High dynamic range (HDR) imaging offers a radically approach of representing colors in digital images. Instead of using the range of colors produced by given devices, HDR imaging method manipulates and stores all colors and brightness levels visible to the human eye. To faithfully represent, store and then reproduce all these effects, the original scene must be stored and treated using high fidelity HDR techniques. Then, tone mapping is required to accommodate HDR image to low dynamic range (LDR) devices, and tone mapping operation of HDR image for realistic display is commonly researched. However, color visualization for analyzing scene luminance in HDR imaging has less attention from researches. This paper presents and implements a method for reproduction and visualization of the false color in HDR images. We produce a color visualization framework with several mapping functions, and evaluate their effectiveness by using RMAE and SNR with commonly used HDR image data. Experiment reveals that the sigmodal mapping function shows better performance in the false color visualization, compared to other methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.36-41
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• 2018

An image intensifying device is equipment that makes weak objects visible in a dark environment, such as making nighttime bright enough to let objects be visually observed. It is possible to obtain a clear image by amplifying the light in the presence of a certain amount of weak light. However, in an extremely low-light environment, where even moonlight is not present, there is not enough light to amplify anything, and the sharpness of the screen deteriorates. In this paper, a method is proposed to improve image quality by using multiple filters and anisotropic diffusion for output noise of the image-intensifying device in extreme low-light environments. For the experiment, the output of the image-intensifying device was obtained under extremely low-light conditions, and signal processing for improving the image quality was performed. The configuration of the filters for signal processing uses anisotropic diffusion after applying a median filter and a Wiener filter for effective removal of salt-and-pepper noise and Gaussian noise, which constitute the main noise appearing in the image. Experimental results show that the improvement visually enhanced image quality. Both peak signal-to-noise ratio (PSNR) and SSIM, which are quantitative indicators, show improved values.

• Restorative Dentistry and Endodontics
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• v.17 no.2
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• pp.307-330
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• 1992

The aim of this study was to investigate the physical properties of visible light curing Glass Ionomer cement for restorative esthetic filling. The control group was the autopolymerizing GC Fuji II Glass Ionomer cement (2.2: 1 P/L ratio) and the experimental groups were made by following procedure. To induce the polymerization by visible light, the powder of GC Fuji II GI cement and the liquid of Vitrabond for base & liner were mixed in an amalgam capsule with 2.5:1, 3.0:1, 3.5:1 P/L ratio (% wt/wt). After fabrication of specimens, compressive strength, fracture toughness ($K_{IC}$) Scanning Electron Microscope and X-ray Diffraction, water-leachable content, marginal leakage and surface roughness were studied. The results were as follows: 1. Only experimental No. 1 group (visible light curing) showed less compressive strength than control group 1 hour after curing. Strength was increased with aging in all groups, so the compressive strength of light curing groups was no less than that of autopolymerizing group after 3 weeks. 2. Experimental No.3 group (visible light curing) was inferior to No.2 group (visible light curing) in fracture resistance but light curing groups were more resistant to fracture than autopolymerizing group and showed ductile fracture pattern as compared with the brittle fracture pattern of autopolymerizing group. 3. From scanning electron microscopic image, various sized unreacted powder particles, surrounded by silica gel, were embedded in polysalt matrix. Light curing groups showed little crack and more dense unreacted particles than autopolymerizing group. 4. From X-ray diffraction analysis, GC Fuji II Glass Ionomer cement powder and all groups showed glassy appearance but light curing groups seemed to be more intensive in crystaline than autopolymerizing group. S. The most significant dissolution was shown in early setting period in all group. Light curing groups were dissolved less than autopolymerizing group. 6. Marginal leakage was not different significantly in case of cavity margin composed of same tooth structure (ex. only enamel margin, only dentin margin) but much more leakage was shown in dentin/cementum margin than enamel margin. In only case of only enamel margin, light curing groups were superior to autopolymerizing group. 7. All groups showed relatively smooth surface, which irregularity was less than $1{\mu}m$. Light curing groups were smoother than autopolymerizing group.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.115-123
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• 2015

The infrared light is known to be less dependent on background light compared to the visible light, and thus many applications such as remote sensing and image surveillance use the infrared image. Similar to color images, infrared images can also be degraded by hazy weather condition, and consequently the performance of the infrared image-based applications can decrease. Nevertheless, infrared image dehazing has not received significant interest. In this paper, we analyze the characteristic of infrared images, especially near-infrared (NIR) images, and present an NIR dehazing algorithm using the analyzed characteristics. In particular, a machine learning framework is adopted to obtain an accurate transmission map and several post-processing methods are used for further refinement. Experimental results show that the proposed NIR dehazing algorithm outperforms the conventional color image dehazing method for NIR image dehazing.

• Proceedings of the Korean Vacuum Society Conference
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• 1997.07a
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• pp.173-176
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• 1997

A numerical analysis of the micro-discharge in an AC pplasma dispplay cell has been made using time-deppendent, 2-dimensional multi-fluid equations to understand the discharge pphysics of He-Xe discharge. The time deppendent distribution of the electron tempperature, densities of electrons, various ions and excited sppecies, and the effects fo the wall charge accumulated on the dielectric surface are obtained and comppared with the results of direct observation of time deppendent behavior of VUV and visible sppectra from single discharge cell observed using a gated, image intensified CCD to elucidate the discharge physics.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.542-545
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• 1990

Texture provides an important source of information about the local orientation of visible surfaces. In this study the 3D shape of a textured surface is recovered from its perspective projection image on the assumption that the texture is homogeneously distributed. To recover 3D structure, the distorting effects of the perspective projection must be distinguished from properties of the texture. In this study, paraperspective projection, approximation of perspective projection, has employed.