Object-specific optimization of hierarchical multiscale segmentations for high-spatial resolution remote sensing images.

Accurate segmentation of high-spatial resolution remote sensing images remains a challenging problem for geographic object-based image analysis. An object-specific optimization method for hierarchical multiscale segmentations is proposed in this study by fusing multiple segmentations into an optimized segmentation with specific consideration of each object. Based on a segment tree model representing hierarchical multiscale segmentations, the framework of object-specific optimization is achieved by identifying and fusing the meaningful nodes in each path originating from a leaf node. Within the optimization framework, an optimization measure for identifying meaningful node is designed according to the maximum change of homogeneity in a path. The proposed optimization method is experimentally validated to hold the advantage of improving segmentation accuracy by the manner of object-specific optimization as well as the potential of automatically producing optimized segmentation for successive object-based analysis. [ABSTRACT FROM AUTHOR]