• 한국측량학회지
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• 제22권4호
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• pp.359-365
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• 2004

많은 응용분야에서 단일 자료가 가진 한계를 극복하기 위해 다중 자료를 이용하여 통합 활용하는 기법이 요구되고 있다. 특히, 서로 다른 공간해상도와 분광해상도를 가진 영상들을 이용하여 영상의 공간해상도를 향상시키는 영상융합과 두 자료간의 상호 관계를 설정하는 영상등록에 대한 많은 연구가 진행되고 있다. 본 연구에서는 IKONOS 전정색 영상과 다중분광 위성영상에 대해 Brovey, IHS, PCA, HPF, CN, MWD 융합기법을 적용하여 원 영상의 분광정보를 가장 적게 왜곡하는 융합기법 에 대해 고찰하였다. 또한, SPOT-5 위성영상과 RADARSAT SAR 위성영상 간에 패치를 이용한 영상정합 기법을 적용하여 해석하였다. 본 연구를 통해 영상 융합에서 시각적 분석 및 통계적 분석 결과 HPF, MWD 융합기법이 가장 좋은 성과를 나타냈었으며, SPOT-5 위성영상과 RADARSAT SAR 위성영상으로부터 지형정보를 세밀하게 표현할 수 있는 패치를 추출함으로써 효과적인 영상등록이 가능하였다.

• 대한원격탐사학회지
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• 제23권5호
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• pp.431-437
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• 2007

Multi-Spectral Camera(MSC) on the KOMPSAT-2 satellite was developed and launched as a main payload to provide 1m of GSD(Ground Sampling Distance) for one(1) channel panchromatic imaging and 4m of GSD for four(4) channel multi-spectral imaging at 685km altitude covering l5km of swath width. Since the compression on MSC image chain was required to overcome the mismatch between input data rate and output date rate JPEG-like method was selected and analyzed to check the influence on the performance. In normal operation the MSC data is being acquired and transmitted with lossy compression ratio to cover whole image channel and full swath width in real-time. In the other hand the MSC performance have carefully been handled to avoid or minimize any degradation so that it was analyzed and restored in KGS(KOMPSAT Ground Station) during LEOP(Launch and Early Operation Phase). While KOMPSAT-2 had been developed, new compression method based upon wavelet for space application was introduced and available for next satellite. The study on improvement of image chain including new compression method is asked for next KOMPSAT which requires better GSD and larger swath width In this paper, satellite image chain which consists of on-board image chain and on-ground image chain including general MSC description is briefly described. The performance influences on the image chain between two on-board compression methods which are or will be used for KOMPSAT are analyzed. The differences on performance between two methods are compared and the better solution for the performance improvement of image chain on KOMPSAT is suggested.

• International Journal of Knowledge Content Development & Technology
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• 제7권1호
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• pp.57-78
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• 2017

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.750-750
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• 2002

The Airship PKNU is a roughly 12 m (32 ft) long blimp, filled with helium, whose two-gasoline power(3hp per engine) are independently radio controlled. The motors and propellers can be tilted and are attached to the gondola through an axle and supporting braces. Four stabilizing fins are mounted at the tail of the airship. To fill in the helium, a valve is placed at the bottom of the hull. The inaugural flight was on jul. 31.2002 at the Pusan, S.korea Most environment monitoring system\ problem use satellite image. But, Low resolution satellite image (multi-spectral) : 1km ∼ 250 m ground resolutions is lows. So, detail information acquisition is hard at the complex terrain. High resolution satellite image (black and white) 30m : The ground resolution is high. But it is high price, visit cycle and delivery time is long So. We want make high accuracy airship photogrammetry system. This airship can catch picture Multi. spectral Aerial photographing (visible, Near infrared and thermal infrared), and High resolution (over 6million pixel). It can take atmosphere datum (Temperature (wet bulb, dew point, general), Pressure (static, dynamic), Humidity, wind speed). this airship is very Quickness that aircraft install time is lower than 30 minutes, it is compact and that conveyance is easy. High-capacity save image (628 cut per 1time (over 6million and 4band(R,G,B,NIR)) and this airship can save datum this High accuracy navigatin (position and rotate angle) by DGPS tech. and Gyro system. this airship will do monitor about red-tide, sea surface temperate, and CH-A, SS and etc.

• 대한원격탐사학회지
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• 제30권2호
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• pp.219-226
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• 2014

분광혼합분석 결과로 얻어지는 각 물체의 점유비율을 활용하면 보다 세밀한 분류가 가능하다. 이는 복잡한 도심지역의 피복분류 뿐만 아니라 혼효림이 많은 한반도 임상분류에 적합한 분류기법이 될 수 있다. 효과적인 임상분류를 위해서는 무엇보다 적절한 endmember의 추출이 선행되어야 하는데, 기존에 주로 사용되었던 기하학적 방법(geometric endmember selection)은 분광특성이 유사한 산림지역에 적합하지 않다. 본 연구에서는 영상에서 직접 순수한 화소를 추출하는 기법 중의 하나인 IEA(Iterative Error Analysis)와 침엽수와 활엽수의 분광특성을 이용하여 실험지역을 대표할 수 있는 각각의 endmember를 자동으로 추출하였다. CASI(Compact Airborne Spectrographic Imager) 영상의 두 지역에 대하여 분광혼합분석을 이용한 분류를 수행한 결과, 분류 정확도는 각각 86%와 90%로, 제안한 기법이 실험대상지역을 대표하는 침엽수와 활엽수의 endmember를 적절하게 추출한 것으로 나타났다. 분광혼합분석 기법을 이용한 보다 효과적인 분류를 위해서 분류항목 외 기타물질을 endmember로 고려하는 연구가 필요할 것으로 보인다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.249-252
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• 2005

Microphytobenthos bloom from late January to early March in Korean tidal flats. KOMPSAT-2 will provide multi-spectral images with a spatial resolution of 4 m comparable with IKONOS. Using IKONOS and Landsat data, algal mat detection was tested in the Saemangeum area~ Micro-benthic diatoms are abundant and a major primary product in the tidal flats. A linear spectral unmixing (LSU) method was applied to the test data. LSU was effective to detect algal mat and the classified algal mat fraction well correlated with NDVI image. Fine grained upper tidal flats are generally known to be the best environment for algal mat. Algal mat thriving in coarse grained lower tidal flats as well as upper tidal flats were reported in this study. A high resolution multi-spectral sensor in KOMPSAT-2 will provide useful data for long-term monitoring of microphytobenthos in tidal flats.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1751-1754
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• 2003

CCD Camera System으로 capture 한 image를 표준 display장치로 재현할 때 capture 할 당시의 원 피사체의 모습을 그대로 재현하여야만 한다. 그러나 일반 consumer 용 camera system의 CCD channel spectral sensitivity 특성이 인간의 spectral sensitivity(1(λ), m(λ), 5(λ)) 특성과 일치하지 않고, linear transform의 관계도 성립하지 않음으로써 capturing시 근본적인 color error가 발생하게 된다. 기존의 CCD Camera System 에서는 CCD sensor 의 color 정보와 display 장치의 color 정보와의 단순한 산술적인 관계로 color를 재구성하는 방법을 사용하고 있어 원 피사체의 color 를 그대로 재현할 수가 없다. 본 논문에서 제시하는 알고리즘은 CCD 의 channel spectral sensitivity특성 과 CIE-color matching function과의 관계를 고려하여 color를 재구성함으로써 color error를 줄이도록 하였다 제시된 알고리즘의 color error를 검증하기 위하여 물체의 고유반사율을 알고 있는 AGFA IT8.7-2 test chart(283 spectra), Dupont Paint Chips(120 spectra), Mcbeth Color Checker(64 spectra) 및 Natural Objects(170 spectra) 등 다양한 objects spectra(637 spectra) [1][2]를 이용하여 기존 방법의 알고리즘과 비교하여 보았다.

• 천문학회지
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• 제47권5호
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• pp.195-199
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• 2014

We present a GUI-based interactive Python program, VIMAP, which generates radio spectral index maps of active galactic nuclei (AGN) from Very Long Baseline Interferometry (VLBI) maps obtained at different frequencies. VIMAP is a handy tool for the spectral analysis of synchrotron emission from AGN jets, specifically of spectral index distributions, turn-over frequencies, and core-shifts. In general, the required accurate image alignment is difficult to achieve because of a loss of absolute spatial coordinate information during VLBI data reduction (self-calibration) and/or intrinsic variations of source structure as function of frequency. These issues are overcome by VIMAP which in turn is based on the two-dimensional cross-correlation algorithm of Croke & Gabuzda (2008). In this paper, we briefly review the problem of aligning VLBI AGN maps, describe the workflow of VIMAP, and present an analysis of archival VLBI maps of the active nucleus 3C 120.

• Journal of the Optical Society of Korea
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• 제18권5호
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• pp.507-516
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• 2014

We present a hybrid method for spectral reflectivity recovery, using 3D extrapolation as a supplemental method for 3D interpolation. The proposed 3D extrapolation is an extended version of 3D interpolation based on the barycentric algorithm. It is faster and more accurate than the conventional spectral-recovery techniques of principal-component analysis and nonnegative matrix transformation. Four different extrapolation techniques (based on nearest neighbors, circumcenters, in-centers, and centroids) are formulated and applied to recover spectral reflectivity. Under the standard conditions of a D65 illuminant and 1964 $10^{\circ}$ observer, all reflectivity data from 1269 Munsell color chips are successfully reconstructed. The superiority of the proposed method is demonstrated using statistical data to compare coefficients of correlation and determination. The proposed hybrid method can be applied for fast and accurate spectral reflectivity recovery in image processing.

• 한국측량학회지
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• 제34권2호
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• pp.121-132
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• 2016

This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regions as those in simulated image by using the UPDM (Universal Pattern Decomposition Method). Simultaneously, shadows cast by buildings or high features under the new sun position were modeled. Then, pixels that changed from shadow into non-shadow areas and vice versa were simulated on the basis of existing images. Finally, buildings that were viewed under the new sensor position were modeled on the basis of open library-based 3D reconstruction program. An experiment was conducted to simulate WV-3 (WorldView-3) images acquired under two different sun-sensor geometries based on a Pleiades 1A image, an additional WV-3 image, a Landsat image, and 3D building models. The results show that the shapes of the buildings were modeled effectively, although some problems were noted in the simulation of pixels changing from shadows cast by buildings into non-shadow. Additionally, the mean reflectance of the simulated image was quite similar to that of actual images in vegetation and water areas. However, significant gaps between the mean reflectance of simulated and actual images in soil and road areas were noted, which could be attributed to differences in the moisture content.