Proc. SPIE. 10609, MIPPR 2017: Pattern Recognition and Computer Vision
KEYWORDS: Image processing algorithms and systems, Digital image processing, Image segmentation, Image processing, Pattern recognition, Remote sensing, Feature extraction, Data processing, Information technology, Binary data
This paper presents a method of segment the river area in remote sensing images. The spectral distribution of the river area in the image is relatively uniform, and the overall gray level is dark, And the spectrum is evenly distributed regardless of direction, but land area spectral information is very messy, most of the land in the regional spectral distribution is not uniform, maybe some land area spectral distribution is more uniform, but has a certain direction, this paper according to these characteristics, using the cross-type template, the regional variance is used as the regional texture characteristic to obtain the adaptive threshold to obtain the adaptive binary graph. The river is usually a connected water, only a large enough area to determine the river, so the use of binary image marking algorithm to obtain the largest connected area, marked as a river. This paper presents the method of river segmentation. Experiments show that the river segmentation is suitable for remote sensing images with relatively large river regions.