Abstract

Remote sensing image river extraction can provide effective data information for flood disaster prevention and control, water resource pollution etc. River extraction of remote sensing image can be regarded as an image segmentation problem. Due to the large amount of information contained in RGB (Red, Green and Blue) color images, the existing remote sensing image river extraction algorithms extract rivers based on grayscale images. However, human eyes have a high recognition for color images, and at the same time, rich information is conducive to more accurate image extraction. In this paper, HSV (Hue, Saturation and value) color image segmentation is used in remote sensing image river segmentation, the RGB color image is converted to HSV color image, H image component and S image component are multiplied, and set the threshold image is multiplied with the original image to obtain the river extraction image. At last, combined with river shape detection extracts the river area and water area from the remote sensing image to obtain a complete river area image.

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