• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5039-5055
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• 2018

The quality of natural outdoor images captured by visible camera sensors is usually degraded by the haze present in the atmosphere. In this paper, a fast image dehazing method based on visible image and near-infrared fusion is proposed. In the proposed method, a visible and a near-infrared (NIR) image of the same scene is fused based on the dual-tree complex wavelet transform (DT-CWT) to generate a dehazed color image. The color of the fusion image is regulated through haze concentration estimated by dark channel prior (DCP). The experiment results demonstrate that the proposed method outperforms the conventional dehazing methods and effectively solves the color distortion problem in the dehazing process.

• 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.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1379-1386
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• 2018

In this paper, we proposed eyeglass type periorbital wrinkle treatment device for reducing and improving periorbital wrinkles using near infrared LED of 850nm wavelength and galvanic current. The proposed periorbital wrinkle treatment device is equipped with a control system based on F-PCB. It consists of eight near-infrared LEDs and four indicator LEDs for treatment of right and left periorbital wrinkles. The eyeglass frame is coated with conductive material, so galvanic current can flow to the skin of periorbital wrinkle contacted to it. One male adult in the mid-40s was allowed to use the device for 10 minutes every day for 4 weeks. After 4 weeks, image analysis using optical equipment for measuring wrinkles indicated that wrinkle indexes were reduced.

• Journal of the Optical Society of Korea
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• v.12 no.2
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• pp.79-87
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• 2008

We have developed a miniature fisheye lens with $190^{\circ}$ field of view operating simultaneously in the visible and the near infrared wavelengths. The modulation transfer function characteristic for the visible wavelength is sufficient for a mega-pixel-grade image sensor. The lens also has a fair resolution in the infrared wavelength region. The calibrated $f-{\theta}$ distortion is less than 5%, and the relative illumination is over 90%. In consequence, a sharp wide-angle image can be obtained which is uniform in brightness over the entire range of field angles. The real image heights for the visible and the near infrared wavelengths have been fitted to polynomial functions of incidence angle with sub-pixel accuracies. Combined with the near equidistance projection scheme of the lens, this lens can be advantageously employed in various image-processing applications requiring a wide-angle lens.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.67-72
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• 2013

Cloud detection and analysis from satellite images has been a topic of research in many atmospheric and environmental studies; however, it still is a challenging task for many reasons. In this paper, we propose a new method for cloud-type classification using fuzzy logic. Knowing that visible-light images of clouds contain thickness related information, while infrared images haves height-related information, we propose a two-layered fuzzy logic based on the input source to provide us with a relatively clear-cut threshold in classification. Traditional noise-removal methods that use reflection/release characteristics of infrared images often produce false positive cloud areas, such as fog thereby it negatively affecting the classification accuracy. In this study, we used the color information from source images to extract the region of interest while avoiding false positives. The structure of fuzzy inference was also changed, because we utilized three types of source images: visible-light, infrared, and near-infrared images. When a cloud appears in both the visible-light image and the infrared image, the fuzzy membership function has a different form. Therefore we designed two sets of fuzzy inference rules and related classification rules. In our experiment, the proposed method was verified to be efficient and more accurate than the previous fuzzy logic attempt that used infrared image features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.208-223
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• 2015

To solve the problem of face recognition with complex changes and further improve the efficiency, a new near-infrared face recognition algorithm which fuses E-GV-LBP and FKNN algorithm is proposed. Firstly, it transforms near infrared face image by Gabor wavelet. Then, it extracts LBP coding feature that contains space, scale and direction information. Finally, this paper introduces an improved FKNN algorithm which is based on spatial domain. The proposed approach has brought face recognition more quickly and accurately. The experiment results show that the new algorithm has improved the recognition accuracy and computing time under the near-infrared light and other complex changes. In addition, this method can be used for face recognition under visible light as well.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.1
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• pp.33-39
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• 2016

Color image dehazing techniques have been extensively studied, and especially the dark channel prior (DCP)-based method has been widely used. Near infrared (NIR) image based applications are also widespread; however, NIR image-specific dehazing techniques have not attracted great interest. In this paper, the characteristics of NIR images are analyzed and compared with the color images' characteristics. The conventional color image dehazing method is also applied to NIR images to understand its effectiveness on different frequency-band signals. Furthermore, we modify the DCP method considering the characteristics of NIR images and show that our proposed method results in improved dehazed NIR images.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1745-1748
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• 2005

Near-infrared spectroscopy (NIRS) can be used to monitor brain activation by measuring changes in the concentration of oxy- and deoxy-hemoglobin (Hb) by their different spectra in the near-infrared range. Because NIRS is a noninvasive, highly flexible and portable device, it is very suitable to study brain activation when a human repeatedly performs a manipulative task, and possibly provides useful information to construct human adaptive mechatronics (HAM). There is some evidence that the dorsolateral prefrontal cortex (DLPFC) plays a major role in working memory and it is proposed that the use of working memory decreases as a human develops manipulative skills. In the present study, we investigated the activation of the dorsolateral prefrontal cortex (DLPFC) of the brain in Brodmann's areas 9 and 46 in drawing tasks to examine whether NIRS can measure the changes of DLPFC activation as a human develops manipulative skills. Subjects performed a mirror image drawing task and a square drawing task by ones' left hands. In the mirror image task the subject drew following a star shape based on a mirror image of it, but square drawing did not involve mirror image and was estimated to be simpler. The changes of the concentration of oxy-Hb was higher in the mirror image drawing than the square drawing in most subjects. The changes of oxy-Hb decreased as the subject repeated the drawing task in most subjects. In conclusion, The activation of DLPFC measured by NIRS can reflect the brain activity in the development of manipulative skills.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.