• Title/Summary/Keyword: Color Sensing

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PRELIMINARY COMS AOCS DESIGN FOR OPTIMAL OPTICAL PAYLOADS OPERATIONS

  • Park, Young-Woong;Park, Keun-Joo;Lee, Hun-Hei;Ju, Gwang-Hyuk;Park, Bong-Kyu
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.290-293
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    • 2006
  • COMS (Communication, Ocean and Meteorological Satellite) shall be operated with two remote sensing payloads, MI (Meteorological Imager) and GOCI (Geostationary Ocean Color Imager). Since both payloads have rotating mechanisms, the dynamic coupling between two payloads is very important considering the pointing stability during GOCI operation. In addition, COMS adopts a single solar wing to improve the image quality, which leads to the unbalanced solar pressure torque in COMS. As a result, the off-loading of the wheel momentum needs to be performed regularly (2 times per day). Since the frequent off-loading could affect MI/GOCI imaging performance, another suboptimal off-loading time needs to be considered to meet the AOCS design requirements of COMS while having margin enough in the number of thruster actuations. In this paper, preliminary analysis results on the pointing stability and the wheel off-loading time selection with respect to MI/GOCI operations are presented.

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Application of SeaWiFS data for assessment of eutrophication in the Pearl River estuary

  • Chen, Chuqun;Li, Xiaobin
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.909-912
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    • 2006
  • In this paper a method for remotely-sensed assessment of eutrophication was experimented. The water samples were collected for analysis of COD (chemical oxygen demand) and nutrients concentration, and the remote sensing reflectance data at the sampling points were synchronously measured using above-water method in two cruises, which were conducted in the Pearl River Estuary in January 2003 and January 2004 respectively. Based on the in-situ data the local algorithms for estimation of concentration of nutrients (P and N) and COD were developed by Partial Least Squares (PLS) regression. The algorithms were then applied to atmospheric-corrected SeaWiFS data and the COD and nutrients concentration in Pearl River Estuary were estimated. And then the assessment of eutrophication was carried out by comparison of the estimated nutrients and COD value with the water quality standard. The results show that the whole estuary is seriously in eutrophication.

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Application of unmanned aerial image application red tide monitoring on the aquaculture fields in the coastal waters of the South Sea, Korea (연근해 양식장 주변 적조 모니터링을 위한 무인항공영상 적용 연구)

  • Oh, Seung-Yeol;Kim, Dae-Hyun;Yoon, Hong-Joo
    • Korean Journal of Remote Sensing
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    • v.32 no.2
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    • pp.87-96
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    • 2016
  • Red tide, causes aquaculture industry the damages in Korea every summer, was usually detected by using satellite, aquaculture information was difficult to detect by using satellite. Therefore, we suggests the method for detecting the red tide using the coastal observation and the product from the unmanned aerial Vehicle. As a result, we obtained the high resolution unmanned aerial Vehicle images, detected the red tide by using the unsupervised classification from the true color images and the simple algorithm from the RGB color images. Compared the previous color images, unmanned aerial Vehicle images were clearly classified the ocean color, we were able to identify the red tide distribution in sea surface. These methods were determined to accurately monitor the red tide distribution on the aquaculture fields in the coastal waters where is established the aquaculture.

A Study on the Evaluation of Clothing Pattern Image by the Personality Type (성격유형에 따른 복식문양 이미지 평가에 관한 연구)

  • 남기선;한명숙
    • The Research Journal of the Costume Culture
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    • v.12 no.1
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    • pp.59-72
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    • 2004
  • The objectives of this study were to investigate the perceptions of Korean female university students for clothing pattern tendency and structural element of clothing pattern image dimension and to find how individual personality type influence the preferred clothing pattern characteristics. For this study, a questionnaire was designed and sent to 600 female university students of Daejeon, Seoul and metropolitan area. The tool used in this study was MBTI(The Myers-Briggs Type Indicator) Form G Korean version and for the analysis of data SPSS 10.0 package were used. 10 representative patterns for this study were floral, dot, stripe, check, animal, abstract & artistic, geometric, vegetable & leaf, paisely, patchwork pattern. The data were analyzed by factor analysis, arithmetic mean, One-Way ANOVA, x²-test. The major findings were as follows: Clothing pattern image dimension perceived by Korean female university students for 10 representative patterns were basic form, deluxe, specialty, and cultural dimension. Among them, basic form and deluxe dimension were major dimensions. In basic form dimension, dot pattern score was high indicating female students perceive it as light, comfortable, clean, cool and simple pattern image. In deluxe dimension, floral pattern scored high and in specialty dimension, abstract and artistic pattern scored high among other pattern image. In cultural dimension, geometric pattern and check pattern scored high. Based on other detailed analysis results, It is concluded that the personality type greatly influence clothing pattern evaluation. For example, in case of color combination of patchwork pattern, there was a difference in color preference depend on a personality type such as sensing(S) or intuition(N). Therefore, sensing personality type preferred adjacent color combination than contrast color combination. Detailed marketing strategy is necessary in planning textile design of merchandise plan.

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Application of SeaWiFS Chlorophyll-a Ocean Color Image for estimating Sea Surface Currents from Geostationary Ocean Color Imagery (GOCI) data (정지궤도 해색탑재체(GOCI) 표층유속 추정을 위한 SeaWiFS 해색자료의 응용)

  • Kim, Eung;Ro, Young-Jae;Jeon, Dong-Chull
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.209-220
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    • 2010
  • One of the most difficult tasks in measuring oceanic conditions is to produce oceanic current information. In efforts to overcome the difficulties, various attempts have been carried out to estimate the speed and direction of ocean currents by utilizing sequential satellite images. In this study, we have estimated sea surface current vectors to the south of the Korean Peninsula, based on the maximum cross-correlation method by using sequential ocean color images of SeaWiFS chlorophyll-a. Comparison of surface current vectors estimated by this method with the geostrophic current vectors estimated from satellite altimeter data and in-situ ADCP measurements are good in that current speeds are underestimated by about 15% and current directions are show differences of about $36^{\circ}$ compared with previous results. The technique of estimating current vectors based on maximum cross-correlation applied on sequential images of SeaWiFS is promising for the future application of GOCI data for the ocean studies.

Development of Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI)의 개발)

  • Cho, Seong-Ick;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Kang, Gm-Sil;Youn, Heong-Sik
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.157-165
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    • 2010
  • In June 2010, Geostationary Ocean Color Imager (GOCI), the world's first ocean color observation satellite will be launched. GOCI is planned for use in real-time monitoring of the ocean environment around Korean Peninsula by daily analysis of ocean environment measurements of chlorophyll concentration, dissolved organic matter, and suspended sediments taken eight times per day for seven years. GOCI primary data will support a fishery information service and red tide forecasting, and ocean climate change research. In this paper, the development background of GOCI, user requirements, GOCI architecture, and the GOCI on-orbit operational concept are explained.

Estimation of Sea Surface Current Vector based on Satellite Ocean Color Image around the Korean Marginal Sea

  • Kim, Eung;Ro, Young-Jae;Ahn, Yu-Hwan
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.816-819
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    • 2006
  • One of the most difficult parameters to measure in the sea is current speed and direction. Recently, efforts are being made to estimate the ocean current vectors by utilizing sequential satellite imageries. In this study, we attempted to estimated sea surface current vector (sscv) by using satellite ocean color imageries of SeaWifs around the Korean Peninsula. This ocean color image data has 1-day sampling interval and spatial resolution of 1x1 km. Maximum cross-correlation method is employed which is aimed to detect similar patterns between sequential images. The estimated current vectors are compared to the surface geostrophic current vectors obtained from altimeter of sea level height data. In utilizing the color imagery data, some limitations and drawbacks exist so that in warm water region where phytoplankton concentration is relatively lower than in cold water region, estimation of sscv is poor and unreliable. On the other hand, two current vector fields agree reasonably well in the Korean South Sea region where high concentration of chlorophyll-a and weak tide is observed. In the future, with ocean color images of shorter sampling interval by COMS satellite, the algorithm and methodology developed in the study would be useful in providing the information for the ocean current around Korean Peninsula.

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Ocean Disaster Detection System(OD2S) using Geostationary Ocean Color Imager(GOCI) (천리안해양관측위성을 활용한 해양 재난 검출 시스템)

  • Yang, Hyun;Ryu, Jeung-Mi;Han, Hee-Jeong;Ryu, Joo-Hyung;Park, Young-Je
    • Journal of Information Technology Services
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    • v.11 no.sup
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    • pp.177-189
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    • 2012
  • We developed the ocean disaster detection system(OD2S) which copes with the occurrences of ocean disasters (e. g. the red and green tide, the oil spill, the typhoon, and the sea ice) by converging and integrating the ocean color remote sensing using the satellite and the information technology exploiting the mass data processing and the pattern recognitions. This system which is based on the cosine similarity detects the ocean disasters in real time. The existing ocean color sensors which are operated in the polar orbit platforms cannot conduct the real time observation of ocean environments because they support the low temporal resolutions of one observation a day. However, geostationary ocean color imager(GOCI), the first geostationary ocean color sensor in the world, produces the ocean color images(e. g. the chlorophyll, the colored dissolved organic matter(CDOM), and the total suspended solid(TSS)), with high temporal resolutions of hourly intervals up to eight observations a day. The evaluation demonstrated that the OD2S can detect the excessive concentration of chlorophyll, CDOM, and TSS. Based on these results, it is expected that OD2S detects the ocean disasters in real time.

Advanced Retinex Algorithm for Image Enhancement (영상 선명화를 위한 개선된 Retinex 알고리즘)

  • Cha, Hyo-Sang;Hong, Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.29-41
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    • 2013
  • The digital camera is impossible to preserve the appearance of a scene containing high dynamic range due to a limitations of the sensing hardware. The Retinex was proposed on the purpose to solve these problems. While the Retinex enhances visibility and color constancy, it sometimes suffers from color distortion, halo effect and reduced global contrast. This paper presents an advanced Retinex algorithm working on the YCbCr color coordinate to reduce the processing time and to improve the global contrast and color. Simulation results show that our algorithm significantly reduces the total processing time, and provide the superior result image by improving the global contrast and color consistency as well as by reducing the halo effect around the boundaries.

Melon Surface Color and Texture Analysis for Estimation of Soluble Solids Content and Firmness

  • Suh, Sang-Ryong;Lee, Kyeong-Hwan;Yu, Seung-Hwa;Shin, Hwa-Sun;Choi, Young-Soo;Yoo, Soo-Nam
    • Journal of Biosystems Engineering
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    • v.37 no.4
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    • pp.252-257
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    • 2012
  • Purpose: The net rind pattern and color of melon surface are important for a high market value of melon fruits. The development of the net and color are closely related to the changes in shape, size, and maturing. Therefore, the net and color characteristics can be used indicators for assessment of melon quality. The goal of this study was to investigate the possibility of estimating melon soluble solids content (SSC) and firmness by analyzing the net and color characteristics of fruit surface. Methods: The true color images of melon surface obtained at fruit equator were analyzed with 18 color features and 9 texture features. The partial least squares (PLS) method was used to estimate SSC and firmness in melons using their color and texture features. Results: In sensing melon SSC, the coefficients of determination of validation (${R_v}^2$) of the prediction models using the color and texture features were 0.84 (root mean square error of validation, RMSEV: 1.92 $^{\circ}Brix$) and 0.96 (RMSEV: 0.60 $^{\circ}Brix$), respectively. The ${R_v}^2$ values of the models for predicting melon firmness using the color and texture features were 0.64 (RMSEV: 4.62 N) and 0.79 (RMSEV: 2.99 N), respectively. Conclusions: In general, the texture features were more useful for estimating melon internal quality than the color features. However, to strengthen the usefulness of the color and texture features of melon surface for estimation of melon quality, additional experiments with more fruit samples need to be conducted.