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Comparison of Different Methods to Merge IRS-1C PAN and Landsat TM Data

IRS-1C PAN 데이터와 Landsat TM 데이터의 종합방법 비교분석

  • Published : 1998.09.01

Abstract

The main object of this study was to prove the effectiveness of different merging methods by using the high resolution IRS(Indian Remote Sensing Satellite)-1C panchromatic data and the multispectral Landsat TM data. The five methods used to merging the information contents of each of the satellite data were the intensity-hue-saturation(IHS), principal component analysis(PCA), high pass filter(HPF), ratio enhancement method and look-up-table(LUT) procedures. Two measures are used to evaluate the merging method. These measures include visual inspection and comparisons of the mean, standard deviation and root mean square error between merged image and original image data values of each band. The ratio enhancement method was well preserved the spectral characteristics of the data. From visual inspection, PCA method provide the best result, HPF next, ratio enhancement, IHS and LUT method the worst for the preservation of spatial resolution.

본 연구에서는 지구자원탐사용 인공위성 화상데이터중에서 공간해상력이 우수한 RS-1C PAN 데이터와 Landsat TM 데이터를 중합(merging)하는데 있어서, 어떤 중합방법이 유효한지를 밝히고자 하였다. 각기 다른 두 화상데이터를 중합하기 위하여 IHS, PCA, HPF, ratio enhanoement 및 LUT방법을 적용하였으며, 이 방법들에 의하여 얻어진 화상들의 평가에 있어서는, 분광반사특성 보존성부분과 공간해상력 부분으로 나누어서 평가하였다. 그 결과 ratio enhancement방법이 분광반사특성의 보존성에 있어서 가장 좋은 결과를 나타내었다. 전체적인 화상의 시각적 판독평가에 있어서는 PCA방법이 다른 방법에 비하여 공간해상력이 우수한 것으로 파악되었으며 다음으로 HPF, ratio enhancement, IHS, LUT방법의 순으로 나타났다.

Keywords

References

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