• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.579-586
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• 2011

It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.150-153
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• 2014

영상 표시 장치에서 대조 이미지의 왜곡 현상을 보완하기 위해 히스토그램 평활화(Histogram Equalization)와 플래토 평활화(Plateau Equalization)가 사용된다. 히스토그램 평활화(Histogram Equalization)를 이용하여 명암대비를 증가 시킬 경우 과도한 이미지의 밝기 변화에 따른 과포화 현상이 발생하며 실시간 시스템에서는 물체 추적에 왜곡 현상이 발생한다. 특히, 적외선 영상(infrared image)과 같이 명암비가 한쪽으로 치우쳐 있는 영상들을 명암비를 개선하기 위해서는 플래토 평활화(Plateau Equalization)와 같은 영상 개선 방법이 필수적이다. 플래토 평활화에서는 임계값을 사용하는 방법이 제시되고 있지만 실험에 의한 최적 임계값을 찾아내는 방식이며, 이 방법은 입력되는 새로운 영상마다 임계값을 실험에 의해 매번 반복해서 도출해야 문제점이 있다. 본 논문에서 제안하는 방법은 과포화 되는 이미지 영역의 문제를 해결하기 위해 제시하는 방법으로 히스토그램 평활화(Histogram Equalization)의 동적 분할하는 알고리즘에 근거하되, 입력 영상에따라 적응적으로 임계값을 설정하는 기법을 제안한다. 실험을 통해 제안하는 방법이 실시간 영상에서 기존의 동적분할 히스토그램에 비해 자연스럽게 명암비를 개선하여 과포화 되거나 중요한 정보를 누락하여 왜곡 되지 않게 자연스러운 화면을 재생하는 방법을 제안한다.

• Atmosphere
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• v.21 no.3
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• pp.285-300
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• 2011

To discriminate and eliminate chaff echoes in radar measurements, a new removal algorithm in two-dimensional reflectivity composite at the height of 1.5 km has been developed by using the brightness temperature($T_B$) obtained from MTSAT-1R. This algorithm utilizes the fact that chaffs are not appeared in infrared satellite data of MTSAT-1R, but detected in radar measurements due to their significant backscattering in the given radar wavelength. The algorithm is evaluated for three different situations: chaff only, chaff mixed with convective storms, and chaff covered with clouds. The algorithm shows excellent performance for the cases of chaff only and chaff mixed with convective storms. However, the performance of the algorithm significantly depends on the presence of clouds. Thus, the statistical analysis of $T_B$ is performed in order to optimize the monthly threshold.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.278-281
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• 2007

The purpose of this study is to develop snow and sea ice detection algorithm in Communication, Ocean and Meteorological Satellite (COMS) meteorological data processing system. Since COMS has only five channels, it is not affordable to use microwave or shortwave infrared data which are effective and generally used for snow detection. In order to estimate snow and sea ice coverage, combinations between available channel data(mostly visible and 3.7 ${\mu}m$) are applied to the algorithm based on threshold method. As a result, the COMS snow and sea ice detection algorithm shows reliable performance compared to MODIS products with channel limitation. Specifically, there is partial underestimation over the complicated vegetation area and overestimation over the area of high level clouds such as cirrus. Some corrections are performed by using water vapor and infrared channels to remove cloud contamination and by applying NDVI to detect more snow pixels for the underestimated area.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.339-351
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• 2016

For the safety of sea, it is important to monitor sea fog, one of the dangerous meteorological phenomena which cause marine accidents. To detect and monitor sea fog, Moderate Resolution Imaging Spectroradiometer (MODIS) data which is capable to provide spatial distribution of sea fog has been used. The previous automatic sea fog detection algorithms were focused on detecting sea fog using Terra/MODIS only. The improved algorithm is based on the sea fog detection algorithm by Wu and Li (2014) and it is applicable to both Terra and Aqua MODIS data. We have focused on detecting spring season sea fog events in the Yellow Sea. The algorithm includes application of cloud mask product, the Normalized Difference Snow Index (NDSI), the STandard Deviation test using infrared channel ($STD_{IR}$) with various window size, Temperature Difference Index(TDI) in the algorithm (BTCT - SST) and Normalized Water Vapor Index (NWVI). Through the calculation of the Hanssen-Kuiper Skill Score (KSS) using sea fog manual detection result, we derived more suitable threshold for each index. The adjusted threshold is expected to bring higher accuracy of sea fog detection for spring season daytime sea fog detection using MODIS in the Yellow Sea.

• Korean Journal of Remote Sensing
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• v.26 no.4
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• pp.387-394
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• 2010

There has been an increasing trend in damaging by the Asian dust in spring. The continuous monitoring of the dust event with IR channels in geostationary satellite is very useful for forecasting and preventing the event. However, the monitoring with the IR channels revealed various problems associated with sensitivity. To eliminate these problems, we introduced a new concept of monitoring by constructing the background threshold values (BTV) and aerosol index (AI). This paper is about to test the reliability of this concept by applying to geostationary satellite, MTSAT-1R.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.546-554
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• 2011

Near targets in the infrared (IR) images have the steady feature for inner region and the transient feature for the boundary region. Based on these features, this paper proposes a new method to extract the fine target shape of near targets in the IR images. First, we detect the boundary region of the candidate targets using the local variance weighted information entropy (WIE) of the original images. And then, a coarse target region can be estimated based on the labeling of the boundary region. For the coarse target region, we use the opening filter with an adaptive structure element to extract the fine target shape. The decision of the adaptive structure element size is optimized for the width information of target boundary by calculating the average WIE in the enlarged windows. The experimental results show that a proposed method has better extraction performance than the previous threshold algorithms.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.546-550
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• 2014

To investigate the minimum near-infrared ray intensity required (quantifiable threshold value) for consistent measurements of axial length (AL) using partial coherence interferometry (PCI), we attached two polarizing lenses (PL) to two types of PCI (IOLmaster, ALscan). The near-infrared ray intensity of PCI was modified by rotating the axis of one PL at intervals of 5 degrees. The right eye of each volunteer was measured three times and the AL and signal-to-noise ratio (SNR) was recorded five times for each measurement. Reduction of light intensity was theoretically estimated using Malus' Law. AL was measured consistently with both IOLmaster and ALscan until they reached 55 degrees (1.33 % of intensity) and 60 degrees (0.77%), respectively (P = 0.343, Log-rank test). In contrast, SNR decreased as light intensity decreased. In addition, to analyze media opacities that precluded measurement of AL, we retrospectively reviewed the medical records of patients unmeasurable by PCI (ALscan) from May to November 2013. Thirty-eight of 473 eyes (8.0%) could not be measured using ALscan due to media opacities, such as severe posterior subcapsular cataract (PSC, 11 eyes), hypermature cataract (9 eyes), and vitreous hemorrhage (18 eyes). The mean grades of vitreous haze and PSC were $7.72{\pm}0.96$ and $4.45{\pm}1.04$, respectively. In conclusion, up to 0.77-1.33% of near-infrared rays decreased, and AL could be measured consistently.

• Proceedings of the KSRS Conference
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• v.2
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• pp.664-667
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at 0.65 ${\mu}m$ $(R_{0.65})$ and the difference in brightness temperature between 3.7 ${\mu}m$ and 11 ${\mu}m$ $(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at 3.7 ${\mu}m$ $(T_{3.7})$, the temperature at 11 ${\mu}m$ $(T_{11})$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the nine airport areas except the Cheongju airport have revealed the accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.373-377
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at $3.7{\mu}m\;(T_{3.7})$, the temperature at $11{\mu}m\;(T_{11}$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the seven airport areas except the Cheongju airport have revealed the accuracy of 50% in the daytime and 70% in the nighttime, based on statistical verification for the independent samples as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.