• Title/Summary/Keyword: WorldView-2 eight band imagery

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WorldView-2 pan-sharpening by minimization of spectral distortion with least squares

  • Choi, Myung-Jin
    • Korean Journal of Remote Sensing
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    • v.27 no.3
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    • pp.353-357
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    • 2011
  • Although the intensity-hue-saturation (IHS) method for pan-sharpening has a spectral distortion problem, it is a popular method in the remote sensing community and has been used as a standard procedure in many commercial packages due to its fast computing and easy implementation. Recently, IHS-like approaches have tried to overcome the spectral distortion problem inherited from the IHS method itself and yielded a good result. In this paper, a similar IHS-like method with least squares for WorldView-2 pan-sharpening is presented. In particular, unlike the previous methods with three or four-band multispectral images for pan-sharpening, six bands of WorldView-2 multispectral image located within the range of panchromatic spectral radiance responses are considered in order to reduce the spectral distortion during the merging process. As a result, the new approach provides a satisfactory result, both visually and quantitatively. Furthermore, this shows great value in spectral fidelity of WorldView-2 eight-band multispectral imagery.

A Study on the Feature Extraction Using Spectral Indices from WorldView-2 Satellite Image (WorldView-2 위성영상의 분광지수를 이용한 개체 추출 연구)

  • Hyejin, Kim;Yongil, Kim;Byungkil, Lee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.5
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    • pp.363-371
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    • 2015
  • Feature extraction is one of the main goals in many remote sensing analyses. After high-resolution imagery became more available, it became possible to extract more detailed and specific features. Thus, considerable image segmentation algorithms have been developed, because traditional pixel-based analysis proved insufficient for high-resolution imagery due to its inability to handle the internal variability of complex scenes. However, the individual segmentation method, which simply uses color layers, is limited in its ability to extract various target features with different spectral and shape characteristics. Spectral indices can be used to support effective feature extraction by helping to identify abundant surface materials. This study aims to evaluate a feature extraction method based on a segmentation technique with spectral indices. We tested the extraction of diverse target features-such as buildings, vegetation, water, and shadows from eight band WorldView-2 satellite image using decision tree classification and used the result to draw the appropriate spectral indices for each specific feature extraction. From the results, We identified that spectral band ratios can be applied to distinguish feature classes simply and effectively.

Land Cover Classification of Coastal Area by SAM from Airborne Hyperspectral Images (항공 초분광 영상으로부터 연안지역의 SAM 토지피복분류)

  • LEE, Jin-Duk;BANG, Kon-Joon;KIM, Hyun-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.1
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    • pp.35-45
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    • 2018
  • Image data collected by an airborne hyperspectral camera system have a great usability in coastal line mapping, detection of facilities composed of specific materials, detailed land use analysis, change monitoring and so forh in a complex coastal area because the system provides almost complete spectral and spatial information for each image pixel of tens to hundreds of spectral bands. A few approaches after classifying by a few approaches based on SAM(Spectral Angle Mapper) supervised classification were applied for extracting optimal land cover information from hyperspectral images acquired by CASI-1500 airborne hyperspectral camera on the object of a coastal area which includes both land and sea water areas. We applied three different approaches, that is to say firstly the classification approach of combined land and sea areas, secondly the reclassification approach after decompostion of land and sea areas from classification result of combined land and sea areas, and thirdly the land area-only classification approach using atmospheric correction images and compared classification results and accuracies. Land cover classification was conducted respectively by selecting not only four band images with the same wavelength range as IKONOS, QuickBird, KOMPSAT and GeoEye satelllite images but also eight band images with the same wavelength range as WorldView-2 from 48 band hyperspectral images and then compared with the classification result conducted with all of 48 band images. As a result, the reclassification approach after decompostion of land and sea areas from classification result of combined land and sea areas is more effective than classification approach of combined land and sea areas. It is showed the bigger the number of bands, the higher accuracy and reliability in the reclassification approach referred above. The results of higher spectral resolution showed asphalt or concrete roads was able to be classified more accurately.