• Title/Summary/Keyword: MNF

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A Study on Fast Extraction of Endmembers from Hyperspectral Image Data (초분광 영상자료의 Endmember 추출 속도 향상에 관한 연구)

  • Kim, Kwang-Eun
    • Korean Journal of Remote Sensing
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    • v.28 no.4
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    • pp.347-355
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    • 2012
  • A fast algorithm for endmember extraction is proposed in this study which extracts min. and max. pixels from each band after MNF transform as candidate pixels for endmember. This method finds endmembers not from the entire image pixels but only from the previously extracted candidate pixels. The experimental results by N-FINDR using a simulated hyperspectral image data and AVIRIS Cuprite image data showed that the proposed fast algorithm extracts the same endmembers with the conventional methods. More studies on the effect of noise and more adaptive criteria in extracting candidate pixels are expected to increase the usability of this method for more fast and efficient analysis of hyperspectral image data.

Comparison between Hyperspectral and Multispectral Images for the Classification of Coniferous Species (침엽수종 분류를 위한 초분광영상과 다중분광영상의 비교)

  • Cho, Hyunggab;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.25-36
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    • 2014
  • Multispectral image classification of individual tree species is often difficult because of the spectral similarity among species. In this study, we attempted to analyze the suitability of hyperspectral image to classify coniferous tree species. Several image sets and classification methods were applied and the classification results were compared with the ones from multispectral image. Two airborne hyperspectral images (AISA, CASI) were obtained over the study area in the Gwangneung National Forest. For the comparison, ETM+ multispectral image was simulated using hyperspectral images as to have lower spectral resolution. We also used the transformed hyperspectral data to reduce the data volume for the classification. Three supervised classification schemes (SAM, SVM, MLC) were applied to thirteen image sets. In overall, hyperspectral image provides higher accuracies than multispectral image to discriminate coniferous species. AISA-dual image, which include additional SWIR spectral bands, shows the best result as compared with other hyperspectral images that include only visible and NIR bands. Furthermore, MNF transformed hyperspectral image provided higher classification accuracies than the full-band and other band reduced data. Among three classifiers, MLC showed higher classification accuracy than SAM and SVM classifiers.

Production of Vitamin $B_{12}$ by Using Protoplast Fusion between Bacillus natto and Bacillus megaterium (Bacillus natto 및 Bacillus megaterium의 원형질체 융합에 의한 Vitamin $B_{12}$의 생산)

  • Jin, Sung-Hyun;Park, Bub-Gyu;Roh, Myung-Hoon;Kim, Dong-Gyu;Ryu, Beung-Ho
    • Korean Journal of Food Science and Technology
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    • v.22 no.6
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    • pp.611-617
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    • 1990
  • This study was conducted to breed a high vitamin $B_{12}$ producer by the fusion of protoplasts between Bacillus natto and Bacillus megaterium. Auxotrophic mutants of Bacillus natto SH-34 ($thr^-try^-rif^r$) and Bacillus megaterium BK-13 ($arg^-ade^-lys^-str^r$) which showed high protease activity and production of vitamin $B_{12}$, respectively, were isolated for the fusion experiment. Protoplasts were induced by incubating the cells with lysis solution containing $500{\mu}/ml$ lysozyme, and the ratio of protoplast and regeneration formation were ranged from 99% and 67%, respectively. Fusion frequencies of fusants between Bacillus natto SH-34 and Bacillus megaterium BK-13 were appeared in the ranges of $1.0{\times}10^{-5}$ under the treatment of 30% PEG 6000 containing 3% PVP. The fusant, MNF-72 showed the highest product yield of $7.85{\mu}g/g-cell\;vitamin\;B_{12}$ in production medium. For the improvement of productivity, the immobilization of fusants with sodium alginate was carried out. In batch and continuous fermentation systems, the productivity were determined to be $0.58{\mu}g/ml.hr\;and\;0.80{\mu}g/ml.hr\;vitamin\;B_{12}$ under optimum condition, respectivity.

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Extraction of Water Depth in Coastal Area Using EO-1 Hyperion Imagery (EO-1 Hyperion 영상을 이용한 연안해역의 수심 추출)

  • Seo, Dong-Ju;Kim, Jin-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.716-723
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    • 2008
  • With rapid development of science and technology and recent widening of mankind's range of activities, development of coastal waters and the environment have emerged as global issues. In relation to this, to allow more extensive analyses, the use of satellite images has been on the increase. This study aims at utilizing hyperspectral satellite images in determining the depth of coastal waters more efficiently. For this purpose, a partial image of the research subject was first extracted from an EO-1 Hyperion satellite image, and atmospheric and geometric corrections were made. Minimum noise fraction (MNF) transformation was then performed to compress the bands, and the band most suitable for analyzing the characteristics of the water body was selected. Within the chosen band, the diffuse attenuation coefficient Kd was determined. By deciding the end-member of pixels with pure spectral properties and conducting mapping based on the linear spectral unmixing method, the depth of water at the coastal area in question was ultimately determined. The research findings showed the calculated depth of water differed by an average of 1.2 m from that given on the digital sea map; the errors grew larger when the water to be measured was deeper. If accuracy in atmospheric correction, end-member determination, and Kd calculation is enhanced in the future, it will likely be possible to determine water depths more economically and efficiently.

Renal Adenoma with Hydronephrosis in a Cat (고양이에서 수신증이 동반된 신선종)

  • Kang, Sang-Chul;Park, Dae-Sik;Hwang, Eui-Kyung;Woo, Gye-Hyeong;Kim, Jae-Hoon
    • Journal of Veterinary Clinics
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    • v.28 no.3
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    • pp.332-335
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    • 2011
  • A 6-year-old castrated male domestic short hair cat with the clinical signs of anorexia and vomiting was admitted to the local animal hospital. Abdominal radiography and ultrasonography revealed renomegaly and severe hydronephrosis in the right kidney. Surgically excised right kidney was submitted for diagnosis. On the cut surface, two milky white masses and severe dilation of renal pelvis were observed. Most of the neoplastic masses were composed of uniform well differentiated tubules lined by a single layer of cuboidal to columnar cells and projected papillae into the lumen. The neoplastic cells were strong positive for cytokeratin (CK) MNF116, but negative for CK 7. Based on the clinical and gross findings, histopathology and immunohistochemistry, this case was diagnosed as papillary renal adenoma with hydronephrosis.

Classification and evaluation of river environment using Hyperspectral images (초분광 영상정보를 활용한 하천환경 분류 및 평가)

  • Han, Hyeong Jun;Lee, Chang Hun;Kang, Joon Gu;Kim, Jong Tae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.423-423
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    • 2019
  • RGB나 다중분광영상은 높은 공간 해상도로 인해 크기가 작은 물질의 클래스를 부여하는데 있어서는 효과적이지만 분광해상도가 낮아 다양한 종류의 지표물 분류 및 분광적으로 미세한 차이를 보이는 대상 체간의 분류에는 한계를 가지고 있다. 그러나 초분광 영상(Hyperspectral Image)은 대상 객체의 분광 반사곡선을 수백개의 연속적인 분광 파장대 영역으로 상세하게 해당 물체의 정보를 취득할 수 있는 기능을 가지고 있다. 최근 국내에서도 초분광 영상을 이용한 토지피복도 작성 및 환경 모니터링 등 다양한 분야에 적용하기 위한 연구가 시도되고 있다. 최근에는 드론과 같은 소형 UAV를 활용하여 경제적인 비용으로 시공간해상도가 높은 영상을 획득하는 것이 가능하게 되었으며 분광정보를 수집하는 영상 장비의 발전으로 드론에 탑재가 가능한 경량의 소형 초분광센서가 개발됨으로써 보다 높은 분광해상도의 영상을 취득할 수 있게 되었다. 본 연구에서는 효율적인 하천환경조사를 위해 UAV를 활용하여 고해상도 초분광 영상을 취득하였으며, 차원축소법과 분류기 적용에 따른 공간 분류 정확도 분석을 통해 하천환경에 대한 분류 및 평가를 실시하였다. 연구지역에서 획득한 초분광 영상은 노이즈로 인한 영향을 줄이고자 MNF와 PCA 기법으로 차원축소를 수행하였으며, MLC(Maximum Likelihood Classification)와 SVM(Support Vector Machine), SAM(Spectral Angle Mapping) 감독분류기법을 적용하여 하천환경특성에 따른 공간분류를 수행하였다. 연구 결과 MNF기법으로 차원 축소한 영상을 적용하여 MLC 감독분류를 수행하였을 때 가장 높은 분류정확도를 얻을 수 있었으나, 일부 클래스 및 수역의 경계와 그림자 공간에서 주로 오분류가 나타나는 것을 확인할 수 있었다.

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Estimation of Water Depth in Coastal Area Using Hyperspectral Satellite Imagery (하이퍼스펙트럴 위성영상을 이8한 연안지역의 수심산정)

  • Lee Jong-Chool;Kim Dae-Hyun;Lee Young-Do;Yu Young-Hwa
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.165-169
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    • 2006
  • Purpose of this research is estimation of water depth by hyperspectral remote sensing in area that access of ship is difficult This research used EO-1 Hyperion satellite imagery. Atmospheric and geometric correction is executed. Compress of band used MNF transforms. Diffuse Attenuation Coefficient of target area is decided in imagery for water depth estimation. Determination of Emdmember in pixel is using Linear Spectral Unmixing techniques. Water depth estimated using this result.

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Spectral Mixture Analysis for Desertification Detection in North-Eastern China

  • Yoon Bo-Yeol;Jung Tae-Woong;Yoo Jae-Wook;Kim Choen
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.419-422
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    • 2004
  • This paper was carried out desertification area change detection from 1980s to 2000s per unit decade using by multitemporal satellite images (Landsat MSS, TM, ETM+). This study aims to use Spectral Mixture Analysis (SMA) to identify and classify study area. Endmembers is selected bare soil, green vegetation (GV), water body using by Minimum Noise Fraction (MNF). Endmembers used to generate increase and decrease images respective from 1980s to 1990s and from 1990s to 2000s. From the analysis of multitemporal change detection for three periods, it was apparent that the area of bare soil increased significantly, with simultaneous decrease of GV and water body. The multitemporal fraction images can be effectively used for change detection. Though there is no field survey dataset, SMA is reliable result of change detection in desertification in China.

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A Study on Linear Spectral Mixing Model for Hyperspectral Imagery with Geometric Method (기하학적 기법을 이용한 하이퍼스펙트럴 영상의 Linear Spectral Mixing모델에 관한 연구)

  • 장은석;김대성;김용일
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.11a
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    • pp.23-29
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    • 2003
  • Detection in remotely sensed images can be conducted spatially, spectrally or both [2]. If the images have high spatial resolution, materials can be detected by using spatial and spectral information, unless we can't see the object embedded in a pixel. In this paper, we intend to solve the limit of spatial resolution by using the hyperspectral image which has high spectral resolution. Therefore, the Linear Spectral Mixing(LSM) Model which is sub-pixel detection algorithm is used to solve this problem. To find class Endmembers, we applied Geometric Model with MNF(Minimum Noise Fraction) transformation. From the result of sub-pixel detection algorithm, we can see the detection of water is satisfied and the object shape cannot be extracted but the possibility of material existence can be identified.

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Man-made Feature Extraction from the Hyperion Sensor Data (Hyperion 센서 데이터를 이용한 지형지물 추출)

  • 서병준;강명호;이용웅;김용일
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.182-186
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    • 2003
  • 일반적으로 영상은 공간, 분광 및 시간 해상력을 바탕으로 고해상과 저해상 영상으로 구분된다. 최근 IKONOS 와 QuickBird 등 공간해상력이 1m 이하인 위성 영상들이 국내에 공급되어 바야흐로 고해상 위성영상을 이용한 다양한 활용분야들이 연구되고 있다. 이에 반하여 고분광해상력을 갖는 하이퍼스펙트럴 영상에 대한 연구는 미흡한 실정이다. 국제적으로는 항공기탑재 센서들을 이용한 다양하고 광범위한 조사분석 연구가 이루어지고 있으나, 국내에서는 장비와 관심의 부재로 인하여 초기적인 연구 단계에 있는 실정이다 하이퍼스펙트럴 센서는 환경, 지질, 목표물 인식 분야에 있어 많은 관심을 받고 있으며 위성탑재 초다중분광센서가 운용되기 시작하면서 연구의 활성화가 더욱 기대되고 있다. 본 연구에서는 EO-1 위성의 Hyperion 센서 데이터를 이용하여 노이즈 제거를 위한 영상 전처리 과정을 실시하고 분광특성에 따른 무감독 분류를 통한 인덱싱 기법과 널리 알려진 분광 라이브러리를 활용한 대상물, 특히 인공지물 추출 기법을 실험하였다. 이를 위하여 MNF(Maximum/Minimum Noise Filtering) 변환 및 분광 매칭(Spectral Matching) 기법, 분광 라이브러리 처리 등을 수행하였다. 결과의 비교를 위하여 동일 지역의 Landsat ETM+ 데이터를 이용하여 상호비교를 통한 검증작업으로서 그 성과를 판단하였다.

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