Bathymetric inversion using multispectral imagery is an effective way to obtain shallow bathymetric information in water but is with relatively low accuracy. This study focuses on the solid disturbance of shallow seafloor substrate variation and proposes an image-segmentation-based method to improve the shallow bathymetry retrieval accuracy. The image is partitioned into different subregions with homogenous substrate properties, and the bathymetric inversion model is constructed separately in each subregion, thus improving the retrieval accuracy. Experimental results of the Ganquan Island region show that the accuracy of the bathymetric inversion was enhanced by 58.1% after image segmentation using muti statistic features.
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