Automatic extraction of rivers from satellite images using image processing techniques

Automatic extraction of water bodies from satellite imagery has been broadly studied for many reasons, including mapping of natural resources (i.e., forest and water resources), drinking water supplies, food production, agricultural planning, and disaster management. With the growth of global warming, it became essential to maintain the sustainable management of these resources for the preservation of human life. Several methods attempted to allocate water bodies from different satellite imagery in both spatial and spectral domains. In this paper, we present an automatic segmentation method to extract the water body from Landsat satellite imagery. The proposed segmentation approach consists of several stages, including histogram stretching, de-correlation, binarization of the image, and clutter removal using morphological operations. The segmentation results are promising.