Identify damaged buildings from high-resolution satellite Imagery in hazard area using differential morphological Profile

Abstract

This paper presets a methodology and results of evaluating damaged building detection algorithms using an object recognition task based on Differential Morphological Profile (DMP) for Very High Resolution (VHR) remotely sensed images. The proposed approach involves several advanced morphological operators among which an adaptive hit-or-miss transform with varying size, shape and gray level of the structuring elements. IKONOS Satellite panchromatic images consisting of pre and post earthquake site of Sichuan area in China were used. Morphological operation of opening and closing with constructions are applied for segmented images. Unsupervised classification ISODATA algorithm is used for the feature extraction and the results comparison with ground truth data, complex urban area before the earthquake gives 76% and same area wracked after the earthquake gives 88% buildings detection on object based accuracy. This work is being extended to extract shadows and non building objects for better classifications of building roof footprints.