• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.82-89
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• 2014

The damage in germanium (Ge) optical window irradiated by a near-infrared continuous wave (CW) laser was studied. Laser-induced heating and melting process were surveyed, and the specific laser power and the irradiance time to melt were estimated by numerical simulation. The experiments were also carried out to investigate the macro and micro structure change on Ge window. Results showed that the surface deformation was formed by melting and resolidification process, the damaged surface had a polycrystalline phase, and the transmittance as an optical performance factor in mid-infrared region was decreased. We confirmed that an abnormal polycrystalline phase and surface deformation effect such as hillock formation and roughness increase reduced the transmittance of Ge window and were the damage mechanism of CW laser induced damage on Ge window.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.554-556
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• 2005

Meteorological imager on the Multi-functional Transport Satellite (MTSAT-IR), which has been operating formally since 28 June 2005, was intercalibrated with a polar orbit satellite [Aqua Moderate Resolution Imaging Spectroradiometer (Aqua/MODIS)] as a well-calibrated instrument. The intercalibration method used in this study was developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS). This was done for the infrared window channels. The differences of MTSAT-IR and MODIS were are -0.26 K for $11\;\mu m-IR$ window channel, 0.40 K for $12\;\mu m-IR$, window channel, and -0.67 K for $6.7\;\mu m-water$ vapor channel.

• Journal of Sensor Science and Technology
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• v.24 no.4
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• pp.264-269
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• 2015

An infrared (IR) bolometer measures the change of resistance by absorbing incident IR radiation and generates a signal as a function of the radiation intensity. Since a bolometer requires temperature stabilization and light filtering except for the infrared rays, it is essential for the device to be packaged meeting conditions that above mentioned. Minimization of heat loss is needed in order to stabilize temperature of bolometer. Heat loss by conduction or convection requires a medium, so the heat loss will be minimized if the medium is a vacuum. Therefore, vacuum packaging for bolometer is necessary. Another important element in bolometer packaging is germanium (Ge) window, which transmits IR radiation to heat the bolometer. To ensure a complete transmittance of IR light, anti-reflection (AR) coatings are deposited on both sides of the window. Although the transmittance of Ge window is high for IR rays, it is difficult to use frequently in low-price IR bolometer because of its high price. In this paper, we fabricated IR window by utilizing silicon (Si) substrate instead of Ge in order to reduce the cost of bolometer packaging. To enhance the IR transmittance through Si substrate, it is textured using Reactive Ion Etching (RIE). The texturing process of Si substrate is performed along with the change of experimental conditions such as gas ratio, pressure, etching time and RF power.

• ETRI Journal
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• v.35 no.1
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• pp.80-88
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• 2013

A passive infrared or pyroelectric infrared (PIR) sensor is mainly used to sense the existence of moving objects in an indoor environment. However, in an outdoor environment, there are often outbreaks of false alarms from environmental changes and other sources. Therefore, it is difficult to provide reliable detection outdoors. In this paper, two algorithms are proposed to reduce false alarms and provide trustworthy quality to surveillance systems. We gather PIR signals outdoors, analyze the collected data, and extract the target features defined as window energy and alarm duration. Using these features, we model target and false alarms, from which we propose two target decision algorithms: window energy detection and alarm duration detection. Simulation results using real PIR signals show the performance of the proposed algorithms.

• Korean Journal of Remote Sensing
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• v.11 no.1
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• pp.31-45
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• 1995

The values of brightness temperature difference (BTD) between 11um and 12um infrared channels may reflect amounts of low-level water vapor and cloud types due to the different absorptivity for water vapor between two channels. A simple method of classifying cloud types at night was proposed. Two-dimensional histograms of brightness temperature of the 11um channel and the BTD between the split window data over subareas around characteristic clouds such as Cb(cumulonimbus), Ci(cirrus), and Sc(stratocumulus) was constructed. Cb, Ci and Sc can be classified by seleting appropriate thresholds in the two-dimensional histograms. And we can see amounts of low-level water vapor in clear area as well as cloud types in cloudy area in the BTD image. The map of cloud types and low-level water vapor generated by this method was compared with 850hPa and 1000hPa relative humidity(%) of numerical analysis data and nephanalysis chart. The comparisons showed reasonable agreement.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.309-324
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• 2008

In this study the retrieval algorithms have been developed to retrieve total precipitable water (TPW) from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) infrared measurements using a physical iterative retrieval method and a split-window technique over East Asia. Retrieved results from these algorithms were validated against Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) over ocean and radiosonde observation over land and were analyzed for investigating the key factors affecting the accuracy of results and physical processes of retrieval methods. Atmospheric profiles from Regional Data Assimilation and Prediction System (RDAPS), which produces analysis and prediction field of atmospheric variables over East Asia, were used as first-guess profiles for the physical retrieval algorithm. We used RTTOV-7 radiative transfer model to calculate the upwelling radiance at the top of the atmosphere. For the split-window technique, regression coefficients were obtained by relating the calculated brightness temperature to the paired radiosonde-estimated TPW. Physically retrieved TPWs were validated against SSM/I and radiosonde observations for 14 cases in August and December 2004 and results showed that the physical method improves the accuracy of TPW with smaller bias in comparison to TPWs of RDAPS data, MODIS products, and TPWs from split-window technique. Although physical iterative retrieval can reduce the bias of first-guess profiles and bring in more accurate TPWs, the retrieved results show the dependency upon initial guess fields. It is thought that the dependency is due to the fact that the water vapor absorption channels used in this study may not reflect moisture features in particular near surface.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.73-80
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• 2019

In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.73-76
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• 2000

A Scene Based Technique(SBT) that corrects linear array infrared detector's nonuniformity is proposed. Basically, this technique dispenses with using temperature references on a linear array infrared detector. To correct the nonuniformity of infrared images, we use three methods. Firstly, we detect bad channels by using the information which is cumulated all the same line pixels. Secondly, a variable window method is applied to compensate more accurately. Thirdly, an adaptive method which updates gain and offset coefficient is used only on a stationary region. These results are demonstrated on a computer simulation with various images. As a result, the nonuniformity is corrected completely, so that images are enhanced and PSNR(peak signal to noise ratio) is improved much.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.260-267
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• 2011

This paper proposes a method for segmenting objects from the background in IR(Infrared) images based on GrabCut algorithm. The GrabCut algorithm needs the window encompassing the interesting known object. This procedure is processed by user. However, to apply it for object recognition problems in image sequences. the location of window should be determined automatically. For this, we adopted the Otsu' algorithm for segmenting the interesting but unknown objects in an image coarsely. After applying the Otsu' algorithm, the window is located automatically by blob analysis. The GrabCut algorithm needs the probability distributions of both the candidate object region and the background region surrounding closely the object for estimating the Gaussian mixture models(GMMs) of the object and the background. The probability distribution of the background is computed from the background window, which has the same number of pixels within the candidate object region. Experiments for various IR images show that the proposed method is proper to segment out the interesting object in IR image sequences. To evaluate performance of proposed segmentation method, we compare other segmentation methods.