• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.89-94
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• 2019

K1A1 tank commander's primary thermal sight is a device that enables tank commanders to detect, identify, aim and track the target by observing targets in all directions during day, night and in situations of smokescreen and fog through $360^{\circ}$ rotation independent from the gunner's primary thermal sight and stabilizing the line of sight even under the vibrations occurring when the tank is standstill and moving. The main function of this device is to detect and process visible and thermal images and deliver the final images to the tank commander. One of the core parts to that end is the observation window (daytime/thermal image window). This core part is mounted at the entrance of the optical path for observing the target and plays the role of making visible light during the daytime and infrared light during the night pass through the target and transmitting the resultant images to the internal optical system of the tank commander's primary thermal sight. Such core parts have been selected as depot maintenance items so that they are replaced by new parts instead of being recycled when they are subjected to maintenance in most cases. That is, the military budget is wasted because such parts are replaced by new parts despite that they can be recycled for maintenance. Therefore, this study proposed a mounting tool for polishing and coating observation windows (daytime and thermal image window) using planar polishing equipment and DLC (Diamond-Like Carbon) coating equipment. In addition, this study presented an amendment (proposal) of the Depot Maintenance Work Request (DMWR) already published to verify the performance of recycled products including the establishment of inspection standards for recycling processes.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1296-1305
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• 2019

To solve the problem of poor noise suppression capability and frequent loss of edge contour and detailed information in current fusion methods, an infrared and visible light image fusion method based on variational multiscale decomposition is proposed. Firstly, the fused images are separately processed through variational multiscale decomposition to obtain texture components and structural components. The method of guided filter is used to carry out the fusion of the texture components of the fused image. In the structural component fusion, a method is proposed to measure the fused weights with phase consistency, sharpness, and brightness comprehensive information. Finally, the texture components of the two images are fused. The structure components are added to obtain the final fused image. The experimental results show that the proposed method displays very good noise robustness, and it also helps realize better fusion quality.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.117.1-117.1
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• 2011

We present the smoothness of mid-infrared sky brightness from the Japanese infrared astronomical satellite, AKARI observations. AKARI monitored the north ecliptic pole (NEP) during its cold phase with nine wavebands from 2.4 to 24 ${\mu}m$, out of which six mid-infrared bands are used in this study. Simple sinusoidal fit to the seasonal variation of the sky brightness shows that the mid-infrared brightness towards the NEP is not affected by small-scale features of the interplanetary dust cloud. We applied the power spectrum analysis to the images to search for the fluctuation of sky brightness. The fluctuation powers at 200 arcsecond are estimated to be at most $1.58{\pm}0.33\;nW\;m^{-2}sr^{-1}$ or 0.13% of the total brightness at $7{\mu}m$ and a tleast $0.64{\pm}0.11\;nW\;m^{-2}sr^{-1}$ or 0.02% at $18{\mu}m$. The residual fluctuations at a few arcminute scales at short mid-infrared wavelengths (7, 9, and 11 ${\mu}m$) are consistent with those expected from the diffuse galactic light. At long mid-infrared wavelengths (15, 18, and 24 ${\mu}m$) the measured fluctuations are comparable to or smaller than the one caused by photon noise and their sources are not identified. We conclude that the upper limit of the fluctuation in the zodiacal light is about 0.02% of the sky brightness.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.550-558
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• 2013

The infrared and visible images are represented by different information due to the different wavelength of the light. The infrared image has thermal information and the visible image has texture information. Desirable results are obtained by fusing infrared and visible information. To enhance a visible image, we extract a weight map from a visible image using saturation, brightness. After that, the weight map is adjusted using thermal information in the infrared image. Finally, an enhanced image is resulted from combining an infrared image and a visible image. Our experiment results show that our proposed algorithm is working well to enhance the smoke in the original image.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.46-55
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• 2006

The purpose of this study is a development of an automatic mosaicing for applying to large number of airborne multispectral images, which reduces manual operation by human. 2436 airborne multispectral images were acquired from DuncanTech MS4100 camera with three bands; green, red and near infrared. LIDAR(LIght Detection And Ranging) data and GPS/INS(global positioning system/inertial navigation system) data were collected with the multispectral images. First, the multispectral images were converted to image patterns by unsupervised classification. Their patterns were compared with those of adjacent images to derive relative spatial position between images. Relative spatial positions were derived for 80% of the whole images. Second, it accomplished an automatic mosaicing using GPS/INS data and unsupervised classification. Since the time of GPS/INS data did not synchronized the time of readout images, synchronized GPS/INS data with the time of readout image were selected in consecutive data by comparing unsupervised classified images. This method realized mosaicing automatically for 96% images and RMSE (root mean square error) for the spatial precision of mosaiced images was only 1.44 m by validation with LIDAR data.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.180-191
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• 2016

When up-scaling algorithms for visible light images are applied to infrared (IR) images, they rarely work because IR images are usually blurred. In order to solve such a problem, this paper proposes an up-scaling algorithm for IR images. We employ adaptive dynamic range encoding (ADRC) as a simple classifier based on the observation that IR images have weak details. Also, since human visual systems are more sensitive to edges, our algorithm focuses on edges. Then, we add pre-processing in learning phase. As a result, we can improve visibility of IR images without increasing computational cost. Comparing with Anchored neighborhood regression (A+), the proposed algorithm provides better results. In terms of just noticeable blur, the proposed algorithm shows higher values by 0.0201 than the A+, respectively.

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.484-489
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• 2014

In this paper, we examined factors that influenced light pollution in Korean national parks during peak and off-peak tourist seasons. Cloud-and moonlight-free nighttime satellite images that were collected during October 2012(for peak season) and January 2013(for off-peak season) by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor were used to estimate the levels of light pollution in 19 national parks (excluding the Bukhansan and Mudeungsan National Parks). Bootstrapping regression analyses were conducted to examine the effects of socioeconomic and policy factors on light pollution in the study national parks for peak and off-peak tourist seasons, separately. The characteristics of light pollution in the national parks varied by season. During the peak tourist season, light pollution in the national parks were affected more by night lights nearby the parks than those within in the parks, while in the off-peak season, light sources in the parks were more important. Scattering of light emitted from hotels and other recreational facilities outside the parks that led to the sky glow effect can be attributed to the greater impact of night lights nearby the parks during the peak season. This result suggests that regulating light pollution nearby the park areas is needed to mitigate light pollution in the national parks, especially in a peak tourist season.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.453-454
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• 2003

Most research materials (data), which are used for the study of digital mapping and digital elevation model (DEM) in the field of Remote Sensing and Aerial Photogrammetry are aerial photographs and satellite images. Additionally, they are also used for National land mapping, National land management, environment management, military purposes, resource exploration and Earth surface analysis etc. Although aerial photographs have high resolution, the data, which they contain, are not used for environment exploration that requires continuous observation because of problems caused by its coastline, as well as single - spectral and long-term periodic image. In addition to this, they are difficult to interpret precisely because Satellite Images are influenced by atmospheric phenomena at the time of photographing, and have by far much lower resolution than existing aerial photographs, while they have a great practical usability because they are mulitispectral images. The PKNU 2 is an aerial photographing system that is made to compensate with the weak points of existing aerial photograph and satellite images. It is able to take pictures of very high resolution using a color digital camera with 6 million pixels and a color infrared camera, and can take perpendicular photographs because PKNU 2 system has equipment that makes the cameras stay level. Moreover, it is very cheap to take pictures by using super light aircraft as a platform. It has much higher resolution than exiting aerial photographs and satellite images because it flies at a low altitude about 800m. The PKNU 2 can obtain multispectral images of visible to near infrared band so that it is good to manage environment and to make a classified diagram of vegetation.

• Journal of Korean Neurosurgical Society
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• v.65 no.4
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• pp.572-581
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• 2022

Objective : Compared to microscopes, exoscopes have advantages in field-depth, ergonomics, and educational value. Exoscopes are especially well-poised for adaptation into fluorescence-guided surgery (FGS) due to their excitation source, light path, and image processing capabilities. We evaluated the feasibility of near-infrared FGS using a 3-dimensional (3D), 4 K exoscope with near-infrared fluorescence imaging capability. We then compared it to the most sensitive, commercially-available near-infrared exoscope system (3D and 960 p). In-vitro and intraoperative comparisons were performed. Methods : Serial dilutions of indocyanine-green (1-2000 ㎍/mL) were imaged with the 3D, 4 K Olympus Orbeye (system 1) and the 3D, 960 p VisionSense Iridium (system 2). Near-infrared sensitivity was calculated using signal-to-background ratios (SBRs). In addition, three patients with brain tumors were administered indocyanine-green and imaged with system 1, with two also imaged with system 2 for comparison. Results : Systems 1 and 2 detected near-infrared fluorescence from indocyanine green concentrations of >250 ㎍/L and >31.3 ㎍/L, respectively. Intraoperatively, system 1 visualized strong near-infrared fluorescence from two, strongly gadolinium-enhancing meningiomas (SBR=2.4, 1.7). The high-resolution, bright images were sufficient for the surgeon to appreciate the underlying anatomy in the near-infrared mode. However, system 1 was not able to visualize fluorescence from a weakly-enhancing intraparenchymal metastasis. In contrast, system 2 successfully visualized both the meningioma and the metastasis but lacked high resolution stereopsis. Conclusion : Three-dimensional exoscope systems provide an alternative visualization platform for both standard microsurgery and near-infrared fluorescent guided surgery. However, when tumor fluorescence is weak (i.e., low fluorophore uptake, deep tumors), highly sensitive near-infrared visualization systems may be required.