• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.4
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• pp.592-604
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• 2019

This study examines the stealth function of sputtered fabric with an infrared thermal imaging camera in terms of the thermal and infrared (IR) transmittance characteristics. Various base fabrics were selected, infrared imaging was performed, and infrared transmittance was measured. By infrared camera experiment it was found that the sample was concealed because it had a similar color to the surroundings when the aluminum layer was directed toward the outside. In addition, a comparison of the infrared thermographic image of the untreated sample and the sputtered sample in the laboratory showed that the difference in ${\Delta}E$ value ranged from 31 to 90.4 and demonstrated effective concealment. However, concealment was not observed in the case of the 3-layer (Nylon-Al-Nylon) model when a sputtered aluminum layer existed between two nylon layers. The direction of the sputtering layer did not affect the infrared transmittance in the infrared transmittance experiment. Therefore, it seems better to interpret the concealing effect in the infrared thermographic images by using thermal transfer theory rather than infrared transmittance theory. We believe that the results of this study will be applicable to developing high performance smart clothing and military uniforms.

• Journal of The Korean Astronomical Society
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• v.29 no.2
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• pp.171-179
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• 1996

We have obtained the J K images of the central region of the globular cluster M3 (NGC5272), using the $256\pm256$ InSb array. We present JK photometry of bright red giant branch stars in the central $2'.2\pm2'.2$ region of M3. The infrared color-magnitude diagrams are presented. The comparison of the red giant branch of M3 with that of M13 confirms that both globular clusters have similar metal abundances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.171-174
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• 2003

This paper is a study on the 3D infrared image enhancement with Stereoscopic algorithm on still infrared image. The adapted stereo method is that the depth is extracted by comparison with right-left image, and the enhanced 3D infrared image by matching based on feature is realized. As the result of experiment this method forced the more smooth edge lines of 3D infrared images.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.2
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• pp.128-134
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• 2014

Infrared thermography is an emerging approach to non-contact, non-intrusive, and non-destructive inspection of various solid materials such as metals, composites, and semiconductors for industrial and research interests. In this study, data processing was applied to infrared thermography measurements to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, raw images were often not appropriate. Thus, various data analysis methods were used at the pre-processing and processing levels in data processing programs for quantitative analysis of defect detection and characterization; these increased the infrared non-destructive testing capabilities since subtle defects signature became apparent. A 3D finite element simulation was performed to verify and analyze the data obtained from both the experiment and the image processing techniques.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.23-30
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• 2016

In this paper, we propose an adaptive histogram projection technique for dynamic range compression and an efficient detail enhancement method which is enhancing strong edge while reducing noise. First, The high dynamic range image is divided into low-pass component and high-pass component by applying 'guided image filtering'. After applying 'guided filter' to high dynamic range image, second, the low-pass component of the image is compressed into 8-bit with the adaptive histogram projection technique which is using global standard deviation value of whole image. Third, the high-pass component of the image adaptively reduces noise and intensifies the strong edges using standard deviation value in local path of the guided filter. Lastly, the monitor display image is summed up with the compressed low-pass component and the edge-intensified high-pass component. At the end of this paper, the experimental result show that the suggested technique can be applied properly to the IR images of various scenes.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.327-329
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• 2017

We report a spatial fluctuation analysis of the sky brightness in the near-infrared from observations towards the north ecliptic pole (NEP) by AKARI at 2.4 and $3.2{\mu}m$. As a follow up study of our previous work on the Monitor field of AKARI, we used NEP deep survey data, which covered a circular area of about 0.4 square degrees, in order to extend fluctuation analysis at angular scales up to 1000". After pre-processing, additional correction procedures were done to correct time varying components and instrumental effects such as MUXbleed. To remove resolved objects, we applied $2{\sigma}$ clipping and point spread function (PSF) subtraction. We finally obtained mosaicked images which can be used for the study of various diffuse emissions in the near-infrared sky and found that there are spatial structures in the mosaicked images using a power spectrum analysis.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.169-176
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• 2012

GPS(Global Positioning System) is widely used for the position estimation of an aerial vehicle. However, GPS may not be available due to hostile jamming or strategic reasons. A vision-based position estimation method can be effective if GPS does not work properly. In mountainous areas without any man-made landmark, a horizon is a good feature for estimating the position of an aerial vehicle. In this paper, we present a new method to estimate the position of the aerial vehicle equipped with a forward-looking infrared camera. It is assumed that INS(Inertial Navigation System) provides the attitudes of an aerial vehicle and a camera. The horizon extracted from an infrared image is compared with horizon models generated from DEM(Digital Elevation Map). Because of a narrow field of view of the camera, two images with a different camera view are utilized to estimate a position. The algorithm is tested using real infrared images acquired on the ground. The experimental results show that the method can be used for estimating the position of an aerial vehicle.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.88-98
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• 2021

Recently, the crime prevention and culprit identification even in a low illuminated environment by CCTV is becoming ever more important. In a low lighting situation, CCTV applications capture images under infrared lighting since it is unobtrusive to human eye. Although the infrared lighting leads to advantage of capturing an image with abundant fine texture information, it is hard to capture the color information which is very essential in identifying certain objects or persons in CCTV images. In this paper, we propose a method to acquire color information through DCGAN from an image captured by CCTV in a low lighting environment with infrared lighting and a method to remove color noise in the acquired color image.

• Journal of The Korean Astronomical Society
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• v.29 no.2
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• pp.245-253
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• 1996

We have analyzed infrared (IR) images of Jupiter which was observed at the McDonald Observatory, Texas, U.S.A., during the P/SHoemaker-LEvy 9 (SL9) impact period and about one week after the last impact. The IR images were obtained on the 2.7m telescope using a NICMOS array with filters to isolate the $1.5{\mu}m\;NH_3\; band,\;the\;2.3{\mu}m\;CH_4\;band,\;the\;2.12{\mu}m\;H_2\;S(0)$ pressure-induced absorption, and the continua at $1.58{\mu}m\;and\;2.0{\mu}m$ (short K-band). All images except those with the $1.58{\mu}m$ continuum filter show bright impact sites against the relatively dark Jovian disk near the impact latitude of about $45^{\circ}$ S. This implies that dusts originated from the impacts reflect the solar radiation at high altitudes before absorbed by stratospheric $CH_4,\;NH_3 \;or\;H_2$. The impact sites observed with the $2.3{\mu}m$ filter are conspicuously bright against a very dark background. The morphology of impact sites, G, L, and H at 2.3 and $2.12{\mu}m$ filters shows clearly an asymmetric structure toward the incident direction of the comet fragments, in agreement with the studies of visible impact images obtained with the Hubble Space Telescope. Comparisons of reflectances of G, L, and H sites with simple radiative transfer models suggest that optically thick dust layers were formed at high altitudes at which methane absorption attenuates incoming sunlight only by about $1\%$. The dust layers in these sites seem to form at about the same altitude regardless of the magnitude of the impacts, but they appear to descend gradually after the impacts. The dust layers have optical depths of 2-5, according to the models.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.