• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2002.10a
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• pp.219-223
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• 2002

Many data fusion techniques have been widely studied, but some methods were hard to apply due to complicated theoretical backgrounds and complexed steps. In this study, we tried to compare the wavelet transform, which has been accepted as the best method in terms of spectral distortion, and other three handy methods, which are available in most commercial software. Four clipped test areas were selected for different spectral information. There is, however, no huge improvement in clipped images except water areas. Overall the wavelet transform are superior in most areas, but the multiplicative method relatively gives good correlation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.139-145
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• 2006

The advantage of the lidar data is in fast acquisition and process time as well as in high accuracy and high point density. However lidar data itself is difficult to classify the earth surface because lidar data is in the form of irregularly distributed point clouds. In this study, we investigated land cover classification using both lidar data and optical image through a supervised classification method. Firstly, we generated 1m grid DSM and DEM image and then nDSM was produced by using DSM and DEM. In addition, we had made intensity image using the intensity value of lidar data. As for optical images, the red, blue, green band of CCD image are used. Moreover, a NDVI image using a red band of the CCD image and infrared band of IKONOS image is generated. The experimental results showed that land cover classification with lidar data and optical image together could reach to the accuracy of 74.0%. To improve classification accuracy, we further performed re-classification of shadow area and water body as well as forest and building area. The final classification accuracy was 81.8%.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.581-591
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• 2010

In this paper, we proposed a new wavelet-based image fusion algorithm, which has advantages in both frequency and spatial domains for signal analysis. The developed algorithm compares the ratio of SAR image signal to optical image signal and assigns the SAR image signal to the fused image if the ratio is larger than a predefined threshold value. If the ratio is smaller than the threshold value, the fused image signal is determined by a weighted sum of optical and SAR image signal. The fusion rules consider the ratio of SAR image signal to optical image signal, image gradient and local variance of each image signal. We evaluated the proposed algorithm using Ikonos and TerraSAR-X satellite images. The proposed method showed better performance than the conventional methods which take only relatively strong SAR image signals in the fused image, in terms of entropy, image clarity, spatial frequency and speckle index.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.215-218
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• 2001

본 연구에서는 저해상도 다분광 영상으로부터 고해상도 다분광 영상을 효과적인 추출하기 위해 인공지능의 한 기법인 신경회로망을 이용하여 중합을 위한 구조를 제안하였고, IKONOS 위성 영상에 적용하여 실험 및 결과를 제시하였다. 실험 결과에서 얻어진 화상은 비교적 좋은 분광특성을 나타내었으며, 향후, 본 연구의 중합방법은 토지 이용분류, 환경감시, 자원조사 등의 많은 분야와 지형공간정보 시스템의 데이터 활용 등 여러분야 응용될 경우 우수한 성능을 제공할 것으로 사료된다.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.81-88
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• 2007

The geometry of satellite image captured by linear CCD sensor is different from that of frame camera image. The fact that the exterior orientation parameters for satellite image with linear CCD sensor varies from scan line by scan line, causes the difference of image geometry between frame and linear CCD sensor. Therefore, we need the epipolar geometry for linear CCD image which differs from that of frame camera image. In this paper, we proposed a method of resampling linear CCD satellite image in epipolar geometry under the assumption that image is not formed in perspective projection but in parallel projection, and the sensor model is a 2D affine sensor model based on parallel projection. For the experiment, IKONOS stereo images, which are high resolution linear CCD images, were used and tested. As results, the spatial accuracy of 2D affine sensor model is investigated and the accuracy of epipolar resampled image with RFM was presented.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.3
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• pp.125-132
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• 2017

Even after applying an image registration, Very High Resolution (VHR) multi-temporal images acquired from different optical satellite sensors such as IKONOS, QuickBird, and Kompsat-2 show a local misalignment due to dissimilarities in sensor properties and acquisition conditions. As the local misalignment, also referred to as Registration Noise (RN), is likely to have a negative impact on multi-temporal information extraction, detecting and reducing the RN can improve the multi-temporal image processing performance. In this paper, an approach to fine registration between VHR multi-temporal images by considering local distribution of RN is proposed. Since the dominant RN mainly exists along boundaries of objects, we use edge information in high frequency regions to identify it. In order to validate the proposed approach, datasets are built from VHR multi-temporal images acquired by optical satellite sensors. Both qualitative and quantitative assessments confirm the effectiveness of the proposed RN-based fine registration approach compared to the manual registration.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.571-582
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• 2015

This paper proposes a scheme to reduce spectral distortion in PAN-sharpening which produces a MultiSpectral image (MS) with the higher resolution of PANchromatic image (PAN). The spectral distortion results from reconstructing spatial details of PAN image in the MS image. The proposed method employs Spectral Adjustment and Anisotropic Diffusion to make a reduction of the distortion. The spectral adjustment makes the PAN-sharpened image agree with the original MS image, but causes block distortion because the spectral response of a pixel in the lower resolution is assumed to be equal to the average response of the pixels belonging to the corresponding area in the higher resolution at a same wavelength. The block distortion is corrected by the anisotropic diffusion which uses a conduct coefficient estimating from a local computation of PAN image. It results in yielding a PAN-sharpened image with the spatial structure of PAN image. GSA is one of PAN-sharpening techniques which are efficient in computation as well as good in quantitative quality evaluation. This study suggests the GSA as a preliminary PAN-sharpening method. Two data sets were used in the experiment to evaluate the proposed scheme. One is a Dubaisat-2 image of $1024{\times}1024$ observed at Los Angeles area, USA on February, 2014, the other is an IKONOS of $2048{\times}2048$ observed at Anyang, Korea on March, 2002. The experimental results show that the proposed scheme yields the PAN-sharpened images which have much less spectral distortion and better quantitative quality evaluation.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.89-100
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• 2010

The aim of this study is to produce land cover maps using satellite imagery with various degrees of high resolution and then compare the accuracy of the image types and categories. For the land cover map produced on a small-scale classification the estuary area around the Nakdong river, including an urban area, farming land and waters, was selected. The images were classified by analyzing the aerial photos taken from KOMPSAT2, Quickbird and IKONOS satellites, which all have a resolution of over 1m to the naked eye. Once all of the land cover maps with different images and land cover categories had been produced they were compared to each other. Results show that image accuracy from the aerial photos and Quickbird was relatively higher than with KOMPSAT2 and IKONOS. The agreement ratio for the large-scale classification across the classification methods ranged between 0.934 and 0.956 for most cases. The Kappa value ranged between 0.905 and 0.937; the agreement ratio for the middle-scale classification was 0.888~0.913 and the Kappa value was 0.872~0.901. The agreement ratio for the small-scale classification was 0.833~0.901 and the Kappa value was 0.813~0.888. In addition, in terms of the degree of confusion occurrence across the images, there was confusion on the urbanized arid areas and empty land in the large-scale classification. For the middle-scale classification, the confusion mainly occurred on the rice paddies, fields, house cultivating area and artificial grassland. For the small-scale classification, confusion mainly occurred on natural green fields, cultivating land with facilities, tideland and the surface of the sea. The findings of this study indicate that the classification of the high resolution images with the naked eye showed an agreement ratio of over 80%, which means that it can be used in practice. The findings also suggest that the use of higher resolution images can lead to increased accuracy in classification, indicating that the time when the images are taken is important in producing land cover maps.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.313-321
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• 2002

Supplying high-resolution satellite image, we take much interest in the update and the revision of digital map and thematic map based on the satellite image. This study presented the possibility of the update and the revision to the existing digital map on a scale of l/5,000 and 1/25,000 to take advantage of the IKONOS satellite image. We performed geometric correction to make use of the ground control points of the existing digital map in IKONOS mono-image and created ortho-image by extracting digital elevation model from three dimensional contour data and altitude on the existing digital map. We revised changed features in the method of screen digitizing by overlapping orthorectified satellite image and existing digital map and flawed features of the unchanged area on the satellite images for positional accuracy analysis. As a result, rectification error is calculated at $\pm$3.35m by RMSE. There is a good possibility of update of digital map under the scale of 1/10,000. It is possible to the update of the large scale digital map over the scale of l/5,000, as if we used the method of stereo image and ground control point surveying.