• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.7-14
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• 2006

Detection and identification of targets from remotely sensed imagery are of great interest for civilian and military application. This paper presents an algorithm for target detection in high spatial resolution imagery based on the spectral and the dimensional characteristics of the reference target. In this algorithm, the spectral and the dimensional information of the reference target is extracted automatically from the sample image of the reference target. Then in the entire image, the candidate target pixels are extracted based on the spectral characteristics of the reference target. Finally, groups of candidate pixels which form isolated spatial objects of similar size to that of the reference target are extracted as detected targets. The experimental test results showed that even though the algorithm detected spatial objects which has different shape as targets if the spectral and the dimensional characteristics are similar to that of the reference target, it could detect 97.5% of the targets in the image. Using hyperspectral image and utilizing the shape information are expected to increase the performance of the proposed algorithm.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.41-47
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• 2006

Detection and identification of targets from remotely sensed imagery are of great interest for civilian and military application. This paper presents an algorithm for target detection in high spatial resolution imagery based on the spectral and the dimensional characteristics of the reference target. In this algorithm, the spectral and the dimensional information of the reference target is extracted automatically from the sample image of the reference target. Then in the entire image, the candidate target pixels are extracted based on the spectral characteristics of the reference target. Finally, groups of candidate pixels which form isolated spatial objects of similar size to that of the reference target are extracted as detected targets. The experimental test results showed that even though the algorithm detected spatial objects which has different shape as targets if the spectral and the dimensional characteristics are similar to that of the reference target, it could detect 97.5% of the targets in the image. Using hyperspectral image and utilizing the shape information are expected to increase the performance of the proposed algorithm.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.79-86
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• 2010

Generally, image fusion is defined as generating re-organized image by merging two or more data using special algorithms. In remote sensing, image fusion technique is called as Pan-sharpening algorithm because it aims to improve the spatial resolution of original multispectral image by using panchromatic image of high-spatial resolution. The pan-sharpened image has been an important task due to various applications such as change detection, digital map creation and urban analysis. However, most approaches have tended to distort the spectral information of the original multispectral data or decrease the spatial quality compared with the panchromatic image. In order to solve these problems, a novel pan-sharpening algorithm is proposed by considering the spectral and spatial characteristics of multispectral image. The algorithm is applied to the KOMPSAT-2 and QuickBird satellite image and the results showed that our method can improve the spectral/spatial quality compared with the existing fusion algorithms.

• ETRI Journal
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• v.33 no.4
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• pp.497-505
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• 2011

Image fusion is a technical method to integrate the spatial details of the high-resolution panchromatic (HRP) image and the spectral information of low-resolution multispectral (LRM) images to produce high-resolution multispectral images. The most important point in image fusion is enhancing the spatial details of the HRP image and simultaneously maintaining the spectral information of the LRM images. This implies that the physical characteristics of a satellite sensor should be considered in the fusion process. Also, to fuse massive satellite images, the fusion method should have low computation costs. In this paper, we propose a fast and efficient satellite image fusion method. The proposed method uses the spectral response functions of a satellite sensor; thus, it rationally reflects the physical characteristics of the satellite sensor to the fused image. As a result, the proposed method provides high-quality fused images in terms of spectral and spatial evaluations. The experimental results of IKONOS images indicate that the proposed method outperforms the intensity-hue-saturation and wavelet-based methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.125-135
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• 2009

Owing to its fast computing capability for fusing images, the FIHS(Fast Intensity Hue Saturation) fusion is widely used for fusion purposes. However, the FIHS fusion also distorts color in the same way such as the IHS(Intensity Hue Saturation) fusion technique. In this paper, a FIHS fusion technique(FIHS-BR) which reduces color distortion by using the ratio of each spectral band and an adaptive FIHS fusion(FIHS-SABR) using spatial information and the ratio of each spectral band are proposed. The proposed FIHS-BR fusion reduces color distortion by adding different spatial detail improvement values for each spectral band. The spatial detail improvement values are derived from the ratio of spectral band. And the proposed FIHS-SABR fusion reduces more color distortion by readjusting the spatial detail improvement values for each spectral band according to the ratio of the spectral bands. The spatial detail improvement values are derived adaptively from the characteristics of spatial information of the local image. To evaluate the performance of the proposed FIHS-BR fusion and FIHS-SABR fusion, a computer simulation is performed for IKONOS remote sensing image. Results from the experiments show that the proposed methods have less color distortion for the forest regions which reveal severe color distortion in the traditional FIHS fusion. From the evaluation results of the characteristics of spectral information for fused image, we show that the proposed methods have best results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.2
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• pp.175-181
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• 2011

In remote sensing, it has been a difficult task to obtain a multispectral image with high spatial resolution because of the technical limitation of satellite sensors. In order to solve these problems, various pansharpening algorithms have been tried and proposed. However, most pansharpened images created by various approaches tend to distort the spectral characteristics of the original multispectral image or decrease the visual sharpness of the panchromatic image. To minimize the spectral distortion of pansharpened image while preserving spatial information of the panchromatic image, a hybrid pansharpening algorithm based on the spatial correlation was proposed. In this paper, we analyzed the spatial and spectral distortion of the hybrid pansharpened images generated by the various spatial correlation methods. In the experiments, we proved that the method by using Laplacian filtering was more efficient than other high frequency extraction algorithms in the viewpoint of spectral distortion and spatial sharpness.

• Proceedings of the Optical Society of Korea Conference
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• 2007.02a
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• pp.68-69
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• 2007

In this paper, the spatial and spectral characteristics of an optical demultiplexer based on a chirp volume holographic grating are presented. The chirp grating is recorded by illuminating the photopolymer film under the interference of a convergent beam and divergent beam. The dependence of the spatial distance on the grating-focusing lens separation is observed. The bandwidth and the crosstalk between two channels with 0.4-nm spectral interval are 0.13 nm and 12 dB, respectively.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.405-409
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• 2007

Each class in remotely sensed imagery has different spectral and spatial characteristics. Natural features have relatively smaller spatial changes than spectral changes. Meanwhile, urban area in which buildings, roads, and cars are included is inclined to face more changes of spatial variation than spectral one. This study aims to propose the new urban complexity index (UCI) based on the 3D DWT computation of remotely sensed imageries considering these characteristics. And then we analyze relation between index and land cover map. The 3DWUCI values are related to class and the indices of urban area are greater than natural area. The proposed UCI could be used to express effectively the standard of urban complexity over a wide area.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.39-54
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• 2012

The objective of this study is to propose efficient data fusion techniques feasible to the KOMPSAT-2 satellite images. The most widely used image fusion techniques, which are the high-pass filter (HPF), the intensity-hue-saturation-based (modified IHS), the pan-sharpened, and the wavelet-based methods, was applied to four KOMPSAT - 2 satellite images having different regional and seasonal characteristics. Each fusion result was compared and analyzed in spatial and spectral features, respectively. Quality evaluation of image fusion techniques was performed in both quantitative and visual analysis. The quantitative analysis methods used for this study were the relative global dimensional error (spatial and spectral ERGAS), the spectral angle mapper index (SAM), and the image quality index (Q4). The results of quantitative and visual analysis indicate that the pan-sharpened method among the fusion methods used for this study relatively has the suitable balance between spectral and spatial information. In the case of the modified IHS method, the spatial information is well preserved, while the spectral information is distorted. And also the HPF and wavelet methods do not preserve the spectral information but the spatial information.

• Journal of Astronomy and Space Sciences
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• v.29 no.4
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• pp.407-411
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• 2012

Space-borne remote sensing is an effective and inexpensive way to identify crop fields and detect the crop condition. We examined the multi-temporal spectral characteristics of rice fields in South Korea to detect their phenological development and condition. These rice fields are compact, small-scale parcels of land. For the analysis, moderate resolution imaging spectroradiometer (MODIS) and RapidEye images acquired in 2011 were used. The annual spectral tendencies of different crop types could be detected using MODIS data because of its high temporal resolution, despite its relatively low spatial resolution. A comparison between MODIS and RapidEye showed that the spectral characteristics changed with the spatial resolution. The vegetation index (VI) derived from MODIS revealed more moderate values among different land-cover types than the index derived from RapidEye. Additionally, an analysis of various VIs using RapidEye satellite data showed that the VI adopting the red edge band reflected crop conditions better than the traditionally used normalized difference VI.