ISPRS-Annals ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprs-annals-IV-3-197-2018 AN IMPROVED UNSUPERVISED IMAGE SEGMENTATION EVALUATION APPROACH BASED ON UNDER- AND OVER-SEGMENTATION AWARE Su Tengfei 1 Inner Mongolia Agricultural University, College of Water Conservancy and Civil Engineering, 010018 Inner Mongolia Hohhot, China 23 04 2018 IV-3 197 204 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-annals.copernicus.org/articles/isprs-annals-IV-3-197-2018.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/isprs-annals-IV-3-197-2018.pdf

In this paper, an unsupervised evaluation scheme for remote sensing image segmentation is developed. Based on a method called under- and over-segmentation aware (UOA), the new approach is improved by overcoming the defect in the part of estimating over-segmentation error. Two cases of such error-prone defect are listed, and edge strength is employed to devise a solution to this issue. Two subsets of high resolution remote sensing images were used to test the proposed algorithm, and the experimental results indicate its superior performance, which is attributed to its improved OSE detection model.