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This project aims to extract Water Bodies from high resolution satellite images. The hyper spectral images contain data about all the features. The objective is to eliminate everything but the water body pixels present in the imagery. When we are discussing about extraction, quality of the output depends mostly on the input image. Several other factors like, clarity of the image, weather of the area being photographed, clouds present in the atmosphere, the time of day, etc. come into play. Different extraction techniques are used for the purpose. Starting with analyzing the Digital Number…mehr

Produktbeschreibung
This project aims to extract Water Bodies from high resolution satellite images. The hyper spectral images contain data about all the features. The objective is to eliminate everything but the water body pixels present in the imagery. When we are discussing about extraction, quality of the output depends mostly on the input image. Several other factors like, clarity of the image, weather of the area being photographed, clouds present in the atmosphere, the time of day, etc. come into play. Different extraction techniques are used for the purpose. Starting with analyzing the Digital Number values for getting the basic idea of the image, this thesis moves towards Thresholding which is considered to be the first step for classification. Analyzing the images is done by calculating their Radiance and Top of Atmosphere Spectral Reflectance values. Different types of Indices like Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Automated Water Extraction Index (AWEI) with shadow (¿sh¿) and non-shadow (¿nsh¿) variants are used for the extraction.
Autorenporträt
Thottempudi Pardhu arbeitet als Assistenzprofessor in der Abteilung für Elektronik und Kommunikationstechnik an der SR University, Warangal. Seine Forschungsinteressen umfassen die RADAR-SignalverarbeitungSandeep Kumar Kavuru arbeitet als Experience Architect und Design Lead bei der U.S. Bank, USA.