A non-seed-based region growing algorithm for high resolution remote sensing image segmentation

Abstract

One of the indispensable prerequisites for high resolution remote sensing image interpretation and processing is successful image segmentation. The algorithm presented in this paper aims for a high efficient image segmentation applicable and adaptable to high resolution remote sensing images. This is achieved by a non-seed-based region growing, which constructs neighbor pairwise pixel stack instead of depending on any seed points. The stack is constructed in increasing order of neighbor pairwise pixel spectral difference which is computed based on 4-connexity. The proposed algorithm carries out region growing according to the merging criterion (i.e. grow formula) and traversal of the stack. We apply the proposed and conventional region growing algorithms to two data sets of ZiYuan-3 (ZY-3) high resolution remote sensing images and analyze the segmentation results based on Carleer evaluation method that manifests high efficient segmentation of the proposed algorithm.