Abstract:

In view of the incomplete and the misidentification of surrounding objects of water extraction in the current global water environment monitoring, this paper takes the Shandong Weihe River as the research object, and the improved watershed segmentation method designed by this paper is adopted. Firstly, the spectral information component of the target water body is extracted as the foreground image, then use the expanded water object as the background image. And the foreground image and the background image are superimposed to generate a marker image. The marker image is used by the watershed transformation to realize the automatic extraction of the water body information. The results of this paper are compared with the watershed algorithm of manual marker seed point in OpenCV, the watershed algorithm based on Canny edge, the watershed segmentation method combined with morphological filtering and labeling. The experimental results show that the algorithm designed in this paper is more automated than the seed point watershed algorithm in OpenCV. And the extracted water body is more complete and accurate. The method in this paper avoids the over-segmentation compared to the Canny edge method. Compared with the method of combining morphological filtering markers, the method is more complete and accurate in extracting the target water body. In conclusion, this paper's method is an automatic and effective method for water body extraction.

Key words: water body extraction, spectral information component, morphological expansion, watershed transformation