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Compressed High Resolution Satellite Image Processing to Detect Water Bodies with Combined Bilateral Filtering and Threshold Techniques

Water body extraction has become an increasingly important source of information for the prediction of heavy flood situations over the last few decades. Several approaches for identifying water bodies from separate High Resolution satellite data with varying spatial, spectral, and temporal characteristics have been developed. The vast amount of data available, supported by open access regulations adopted by many agencies, is transforming the remote sensing environment, underlining the necessity of data processing speed and efficiency. The current study presents an autonomous method for extracting water bodies from satellite pictures that use a single-band threshold approach with bilateral filtering. One important goal is to use low-cost software to understand raw picture data to evaluate multi-temporal and multi-sensor images. Using the proposed framework, the workflow is constructed on a free and open-source software processing framework. Water was detected properly and quickly from other land cover features.