River extraction from satellite image
Satellite image processing plays a crucial role for the
research developments in many fields of study including
Astronomy, Remote Sensing, GIS, Agriculture Monitoring
and Disaster Management. The remote sensing images are
utilized in many of the researches with the aim of predicting
natural disasters so that essential precautions can be taken to
protect the environment. Besides the other, the water
resource analysis plays a vital role in these researches.
Traditionally, lots of methods are utilized for the analysis
and determine some resources like water which are
becoming extinct in nature. In this work, the methods like
edge detection, thresholding, image erosion and other color
and feature extraction algorithms are presented to extract
water content (river). The algorithms used here includes, K
means clustering algorithm, Hill Climbing Algorithm, Color
histogram and image thresholding. Here, the condition of
river like normal, drought or flood is also predicted by
visual inspection of the processed satellite image.
Keywords: Binary Thresholding, Hill Climbing Algorithm and K means clustering algorithm
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