Method of segmenting river from remote sensing image

Qingyun Tang; Jun Zhang; Daimeng Zhang; Xiaomao Liu; Jinwen Tian

doi:10.1117/12.2283228

8 March 2018 Method of segmenting river from remote sensing image

Qingyun Tang, Jun Zhang, Daimeng Zhang, Xiaomao Liu, Jinwen Tian

Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 106090C (2018) https://doi.org/10.1117/12.2283228
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China

Abstract

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.

Citation Download Citation

Qingyun Tang, Jun Zhang, Daimeng Zhang, Xiaomao Liu, and Jinwen Tian "Method of segmenting river from remote sensing image", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106090C (8 March 2018); https://doi.org/10.1117/12.2283228

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