BBAuthors: Liu, Y.; Advisor: -; Participants: - (2016)
To create image objects for subsequent classification in object-based image analysis, an optimal segmentation threshold (OST) is a pre-requisite for image segmentation. However, an OST is practically acquired by assessing and ranking an exhaustive segment data stack constructed after foregoing image segmentation. In this paper, we propose an iterative exploration method via recognition of the Euclidean distance 2 (ED2)–scale parameter (SP) pattern with the least five tiles of segment data stack in each cycle among the Potential Segmentation Error (PSE)–Number-of-Segments Ratio (NSR)–ED2 patterns along with SP. We conducted two experiments. In the first experiment, we validated the gen... 
