Semantic segmentation method and system for high-resolution remote sensing image based on random blocks

摘要

A semantic segmentation method and system for a high-resolution remote sensing image based on random blocks. In the semantic segmentation method, the high-resolution remote sensing image is divided into random blocks, and semantic segmentation is performed for each individual random block separately, thus avoiding overflow of GPU memory during semantic segmentation of the high-resolution remote sensing image. In addition, feature data in random blocks neighboring each random block incorporated into the process of semantic segmentation, overcoming the technical shortcoming that the existing segmentation method for the remote sensing image weakens the correlation within the image. Moreover, in the semantic segmentation method, semantic segmentation is separately performed on mono-spectral feature data in each band of the high-resolution remote sensing image, thus enhancing the accuracy of sematic segmentation of the high-resolution remote sensing image.