Second Generation Multi-Resolution Techniques for Edge Detection and Feature Extraction from 8-Bands High Resolution Satellite Imagery
Date
2012-11-30
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Abstract
Urban mapping is one of the most important tasks in military and civilian applications. Since the launching of high resolution satellite imagery; such as IKONOS, QUICKBIRD, WorldView-2 and their high spatial and high spectral resolution are much appreciated for urban mapping, as high spatial resolution provides better geometric quality while high spectral resolution provides better object identification. If we add the reliability and unmatched coverage area, compared to other sensors, with the previous advantages so we are using the optimum tool for urban planning and mapping purposes.
Current scientific efforts in image and signal processing fields have led to more powerful and reliable tools for fast and efficient analysis and handling of large amounts of data sets currently available from the new satellite missions. This thesis contributes to this development by introducing an innovative combination of various methods from image processing and the new eight bands from the WorldView-2 to derive reliable information for land use and land cover types.
In this thesis, data from WorldView-2 satellite for Ismailia city, EGYPT, is used. The study area was selected to cover the main necessary classes to produce an urban classification map. A new multi-layer classification algorithm using the traditional NDVI and two new NDVI like ratio were used to separate between six main classes; water, vegetation, shadow, bare soil, asphalt and buildings.
A new technique based on second generation curvelet transforms was used to detect edges and was compared with wavelet and traditional canny operator. Both approaches; the multi-layer classification algorithm and curvelet transforms, were integrated to enhance the quality of the classification. A calibration process preceded the proposed algorithms and succeeded together in extracting the desired classes with a high accuracy in an almost automatic procedure without user intervention.
Shorelines were also extracted using the new algorithm and the relative bathymetry of the water way of the Suez Canal and the Temsah Lake were derived using innovated band ratios with the new spectral bands.
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Keywords
Remote Sensing, Environmental Sciences
Citation
ELSHARKAWY, AHMED. SHAWKY. (2012). Second Generation Multi-Resolution Techniques for Edge Detection and Feature Extraction from 8-Bands High Resolution Satellite Imagery (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27725