• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.515-523
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• 2018

In order to obtain consistent change detection result for multi-temporal satellite images, preprocessing must be performed. In particular, the preprocessing related to the spectral values can be performed by the radiometric normalization, and relative radiometric normalization is generally utilized. However, most relative radiometric normalization methods assume a linear relationship between the two images, and nonlinear spectral characteristics such as phenological differences are not considered. Therefore, this study proposes a relative radiometric normalization which assumes nonlinear relationships that can perform compositive normalization of radiometric and phenological characteristics. The proposed method selects the subject and reference images, and then extracts the radiometric control set samples through the no-change method. In addition, spectral indexes as well as pixel values are extracted in order to consider sufficient information, and modeling of nonlinear relationships is performed through multilayer perceptron. Finally, the proposed method is compared with the conventional relative radiometric normalization methods, which shows that the proposed method is visually and quantitatively superior.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.999-1011
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• 2021

In spatio-temporal fusion aiming at predicting images with both high spatial and temporal resolutionsfrom multi-sensor images, the radiometric inconsistency between input multi-sensor images may affect prediction performance. This study investigates the effect of radiometric correction, which compensate different spectral responses of multi-sensor satellite images, on the spatio-temporal fusion results. The effect of relative radiometric correction of input images was quantitatively analyzed through the case studies using Sentinel-2, PlanetScope, and RapidEye images obtained from two croplands. Prediction performance was improved when radiometrically corrected multi-sensor images were used asinput. In particular, the improvement in prediction performance wassubstantial when the correlation between input images was relatively low. Prediction performance could be improved by transforming multi-sensor images with different spectral responses into images with similar spectral responses and high correlation. These results indicate that radiometric correction is required to improve prediction performance in spatio-temporal fusion of multi-sensor satellite images with low correlation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.209-219
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• 2019

Satellite imagery occurs geometric and radiometric errors due to external environmental factors at the acquired time, which in turn causes false-alarm in change detection. These errors should be eliminated by geometric and radiometric corrections. In this study, we propose a methodology that automatically and simultaneously performs geometric and radiometric corrections by using the SURF (Speeded-Up Robust Feature) algorithm and the mask filter. The MPs (Matching Points), which show invariant properties between multi-temporal imagery, extracted through the SURF algorithm are used for automatic geometric correction. Using the properties of the extracted MPs, PIFs (Pseudo Invariant Features) used for relative radiometric correction are selected. Subsequently, secondary PIFs are extracted by generated mask filters around the selected PIFs. After performing automatic using the extracted MPs, we could confirm that geometric and radiometric errors are eliminated as the result of performing the relative radiometric correction using PIFs in geo-rectified images.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.917-927
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• 2020

The Ministry of Land, Infrastructure and Transport of Korea is developing a CAS 500-1/2 satellite capable of photographing a GSD 0.5 m level image, and is developing a technology to utilize this. Therefore, this study attempted to develop a geospatial feature extraction technique aimed at automation as a technique for utilizing CAS 500-1/2 satellite images. KOMPSAT-3A satellite images that are expected to be most similar to CAS 500-1/2 were used for research and the possibility of automation of geospatial feature extraction was analyzed through relative radiometric normalization. For this purpose, the parameters and thresholds were applied equally to the reference images and relative radiometric normalized images, and the geospatial feature were extracted. The qualitative analysis was conducted on whether the extracted geospatial feature is extracted in a similar form from the reference image and relative radiometric normalized image. It was also intended to analyze the possibility of automation of geospatial feature extraction by quantitative analysis of whether the classification accuracy satisfies the target accuracy of 90% or more set in this study. As a result, it was confirmed that shape of geospatial feature extracted from reference image and relative radiometric normalized image were similar, and the classification accuracy analysis results showed that both satisfies the target accuracy of 90% or more. Therefore, it is believed that automation will be possible when extracting spatial objects through relative radiometric normalization.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.213-218
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• 2008

동일 지점을 촬영한 위성영상은 위성의 센서나 영상의 취득 시기, 지형의 상태 등에 따라 그 지점에 나타나는 화소값이 일정하지 않다. 이러한 영상은 영상간 모자이크나 변화 탐지 결과에 영향을 미칠 가능성이 높으므로 방사보정(또는 방사정규화)을 통해 화소값의 차이를 최소화시킬 필요가 있다. 본 연구는 선형회귀식을 적용한 상대 방사정규화에 초점을 맞추고 있으며, 선형회귀식 구성에 필요한 PIF(Pseudo Invariant Feature)를 자동으로 추출하기 위해 Ordinal Rank 알고리즘을 적용하였다. 이 방법을 통해 각 밴드별 후보 PIF를 추출하고, 공통으로 해당되는 최종 PIF를 추출할 수 있었다. RMSE(Root Mean Square Error), Dynamic range, Coefficient of variation 등을 통해 방사보정 후의 결과를 평가해보았다. 영상회귀를 이용한 방사보정알고리즘과의 비교를 통해 제안된 알고리즘이 갖는 장점을 확인하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.129-137
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• 2008

This study focuses on the radiometric normalization, which is one of the pre-processing steps to apply the change detection technique fur hyperspectral images. The PIFs which had radiometric consistency under the time interval were automatically extracted by applying spectral angle, and used as sample pixels for linear regression of the radiometric normalization. We also dealt with the problem about the number of PIFs for linear regression with iteratively quantitative methods. The results were assessed in comparison with image regression, histogram matching, and FLAASH. In conclusion, we show that linear regression method with PIFs can carry out the efficient result for radiometric normalization.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2016.10a
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• pp.525-526
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• 2016

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.28.2-28.2
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• 2010

영상레이더 위성으로부터 획득된 SAR 영상의 상대적/절대적 방사(radiometric) 정밀도를 만족시키기 위해서는 궤도상에서 검보정을 수행하여야 한다. 일반적으로 상대 방사 정밀도의 보정을 위해서는 아마존 일대와 같이 일정한 지표 반사도를 지니는 넓은 지역을 촬영함으로써, 지상에서 모델링된 안테나 패턴의 이상 유무를 검증한다. 절대 방사 정밀도를 결정하기 위해서는 보정계수(calibration constant)를 구해야 하는데, 이를 위해서 RCS(radar cross section) 값이 기 알려져 있는 지상의 CR(corner reflector)를 관측해야 한다. 대부분의 SAR 위성의 경우, 각 입사각별로 여러 개의 빔(beam)이 독립적으로 운용되고, 위성의 경로가 각 pass 사이 거의 일정한 간격을 가지기 때문에, 지상의 CR들에 대한 빔의 접근성이 상당히 제약을 많이 받게 된다. 즉, 개별 빔이 촬영할 수 있는 CR의 개수 및 동일 CR에 대한 촬영 빈번도가 많이 작을 수 있다는 것을 의미한다. 특히, CR이 빔폭의 중심에서 관측되어야 하는 요구사항이 추가로 반영될 경우 그 빈도수는 더욱더 영향을 받게된다. 이 연구에서는 고도 550 km, 28일의 지상반복주기(repeat ground track)를 가지는 여명 궤도(dawn-dusk orbit)를 가정하고, 각 빔별로 그 빔에 할당된 하나의 CR만을 촬영해야 된다는 조건하에, 빔 접근성의 요구사항을 최대로 만족시킬 수 있는 CR의 좌표들을 구하였다. 동시에, J2항만을 고려한 이상적 28일 지상반복궤도를 적용한 경우와 모든 중력섭동항을 적용한 최적궤도를 적용한 경우를 비교하여, 실질적 검보정 일정을 수립하였다.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1179-1185
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• 2017

The KOMPSAT-3A satellite acquires high-resolution MWIR images twice a day compared to conventional Earth observing satellites. New radiometric information of Earth's surface can be provided due to different characteristics from existing SWIR images or TIR images. In this study, the difference image of multitemporal images was generated and compared with existing infrared images to find the characteristics of KOMPSAT-3A MWIR satellite images. A co-registration was performed and the difference between pixel values was minimized by using PIFs (Pseudo Invariant Features) pixel-based relative normalization. The experiment using Sentinel-2 SWIR image, Landsat 8 TIR image, and KOMPSAT-3A MWIR image showed that the distinction between artifacts in the difference image of KOMPSAT-3A is prominent. It is believed that the utilization of KOMPSAT-3A MWIR images can be improved by using the characteristics of IR image.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.5 s.347
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• pp.176-181
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• 2006

We have built the close range Dicke type radiometer with 35GHz of frequency, which consists of two stage low noise amplifier and diode detector to calibrate temperatures of materials. We have present thermal calibration methods using millimeter-wave radiometer. Output voltages linearly increase with temperatures between 299K and 309K. We are able to measure lower temperature using the liquid nitrogen although results are somewhat unstable.