• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.517-526
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• 2015

Among the various image fusion or pan-sharpening methods, those wavelet-based methods provide superior radiometric quality. However, the fusion processing is not only simple but also flexible, since many low- and high-frequency sub-bands are often produced in the wavelet domain. To address this issue, a novel DT-CWT (Dual-Tree Complex Wavelet Transform) proportional to the fusion method by a WZP (Wavelet Zero-Padding) is proposed. The proposed method produces a single high-frequency image in the spatial domain that is injected into the LRM (Low-Resolution Multispectral) image. Thus, a wavelet domain fusion can be simplified to spatial domain fusion. In addition, in the proposed DT-CWTP (DT-CWT Proportional) fusion method, it is unnecessary to decompose the LRM image by adopting WZP. The comparison indicates that the proposed fusion method is nearly five times faster than the DT-CWT with SW (Substitute-Wavelet) fusion method, meanwhile simultaneously maintaining the radiometric quality. The conducted experiments with WorldView-2 satellite images demonstrated promising results with the computation efficiency and fused image quality.

• Korean Journal of Remote Sensing
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• v.2 no.2
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• pp.107-116
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• 1986

A unique approach to access Landsat satellite imagery has been implemented on IBM PC microcomputer in order to generate image maps to be used as a substitute and/or supplement for a conventional topographic map. This method enables user to automatically: o extract a nominal image map, o geoencode or calibrate as an image map, and o create a multitemporal image file using CCTs containing precision processed Landsat MSS and TM images. These map extraction process includes: o location of map area in the selected CCT, o conversion of map coordinates to image coordinates, o extraction of map area, and o rotation of image to the true North/South and East/Weat direction.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.183-194
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• 1999

The Brightness, color and texture included in a multispectral satellite data are used as important factors to analyze and to apply the image data for a proper use. One of the most significant process in the satellite data analysis using texture or color information is to extract features effectively expressing the information of original image. It was described in this paper that six features were introduced to extract useful features from the analysis of the satellite data, and also a classification network using the back-propagation neural network was constructed to evaluate the classification ability of each vector feature in SPOT imagery. The vector features were adopted from the training set selection for the interesting region, and applied to the classification process. The classification results showed that each vector feature contained many merits and demerits depending on each vector's characteristics, and each vector had compatible classification ability. Therefore, it is expected that the color and texture features are effectively used not only in the classification process of satellite imagery, but in various image classification and application fields.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.24-33
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• 2004

Advances in remote sensing technologies are resulting in the rapid increase of the number of spectral channels, and thus, growing data volumes. This creates a need for developing faster techniques for processing such data. One application in which such fast processing is needed is the dimension reduction of the multispectral data. Principal component transformation is perhaps the mostpopular dimension reduction technique for multispectral data. In this paper, we discussed the processing procedures of principal component transformation. And we presented and discussed the results of the principal component transformation of the multispectral data. Moreover principal components image data are classified by the Maximum Likelihood method and Multilayer Perceptron method. In addition, the performances of two classification methods and data reduction effects are evaluated and analyzed based on the experimental results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.75-86
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• 2012

Synthetic Aperture Radar(SAR) imaging system is independent of solar illumination and weather conditions; however, SAR image is difficult to interpret as compared with optical images. It has been increased interest in multi-sensor fusion technique which can improve the interpretability of $SAR^{\circ\circ}$ images by fusing the spectral information from multispectral(MS) image. In this paper, a multi-sensor fusion method based on high-frequency extraction process using Fast Fourier Transform(FFT) and outlier elimination process is proposed, which maintain the spectral content of the original MS image while retaining the spatial detail of the high-resolution SAR image. We used TerraSAR-X which is constructed on the same X-band SAR system as KOMPSAT-5 and KOMPSAT-2 MS image as the test data set to evaluate the proposed method. In order to evaluate the efficiency of the proposed method, the fusion result was compared visually and quantitatively with the result obtained using existing fusion algorithms. The evaluation results showed that the proposed image fusion method achieved successful results in the fusion of SAR and MS image compared with the existing fusion algorithms.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.59-65
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land using the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSA T-l) and the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data, this paper compares the results of Intensity Hue Saturation (IHS) and Principal Component Analysis (PCA) methods. The comparison is made by statistical and visual evaluation of three-color combination images of IHS and PCA results based on spatial and spectral characteristics. The use of MODIS bands 1, 2, and 3 with a contrast stretched EOC panchromatic image as a substitute for intensity was found to be particularly effective in this study.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.110-112
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• 2003

The researchers, who seek geological and environmental information, depend on the remote sensing and aerial photographic datum from various commercial satellites and aircraft. However, the adverse weather conditions and the expensive equipment can restrict that the researcher can collect their data anywhere and any time. To allow for better flexibility, we have developed a compact, a multispectral automatic Aerial photographic system. This system's Multi-spectral camera can catch the visible (RGB) and infrared (NIR) bands (3032${\ast}$2008 pixel) image. Our system consists of a thermal infrared camera and automatic balance control, and it managed and controlled by a palm-top computer. And it includes a camera gimbals system, GPS receiver, weather sensor and etc. As a result, we have successfully tested its ability to acquire aerial photography, weather data, as well as GPS data, making it a very flexible tool for environmental data monitoring.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.4
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• pp.359-365
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• 2004

Data integration techniques are becoming increasing1y important for conquering a limitation with a single data. Image fusion which improves the spatial and spectral resolution from a set of images with difffrent spatial and spectral resolutions, and image registration which matches two images so that corresponding coordinate points in the two images correspond to the same physical region of the scene being imaged have been researched. In this paper, we compared with six image fusion methods(Brovey, IHS, PCA, HPF, CN, and MWD) with panchromatic and multispectral images of IKONOS and developed the registration method for applying to SPOT-5 satellite image and RADARSAT SAR satellite image. As the result of tests on image fusion and image registration, we could find that MWD and HPF methods showed the good result in term of visual comparison analysis and statistical analysis. And we could extract patches which depict detailed topographic information from SPOT-5 and RADARSAT and obtain encouraging results in image registration.

• Korean Journal of Remote Sensing
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• v.19 no.2
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• pp.170-179
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• 2003

In order to classify Land Use/Land Cover using multispectral images, we have to give consequence to defining proper classes and selecting training sample with higher class separability. The process of satellite hyperspectral image which has a lot of bands is difficult and time-consuming. Furthermore, classification result of hyperspectral image with noise is often worse than that of a multispectral image. When selecting training fields according to the signatures in the study area, it is difficult to calculate covariance matrix in some clusters with pixels less than the number of bands. Therefore in this paper we presented an overview of feature extraction methods for classification of Hyperion data and examined effectiveness of feature extraction through the accuracy assesment of classified image. Also we evaluated the classification accuracy of optimal meaningful features by class separation distance, which is also a method for band reduction. As a result, the classification accuracies of feature-extracted image and original image are similar regardless of classifiers. But the number of bands used and computing time were reduced. The classifiers such as MLC, SAM and ECHO were used.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.390-395
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• 1999

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.