Improving semantic orthophotos by a fast method based on harmonic inpainting

Abstract

Context-based modeling of 3D urban terrain has become increasingly popular in the last two decades. Typically, orthophotos are used for texturing ground. In order to increase locational awareness, it is useful to eliminate from the orthophotos those object instances which frequently appear and disappear in the terrain. Vehicles are good examples of such instances. Assuming that vehicles were detected at a previous stage of the algorithm, we developed a simple, easily parallelizable procedure on orthophoto inpainting while considering classes of the surrounding objects. This is done by reducing the weights of pixels which should not be used for inpainting. The benefits of our approach are demonstrated for two datasets by comparison with a state-of-the-art method and by integrating the corrected orthophoto into the already existing urban terrain model which moreover includes the ground surface as well as 3D models of buildings, trees and vehicles

Towards Detection of Thermal Anomalies in Large Urban Areas Using Simulation

“…In order to perform the image-based comparison to the simulation, the missing area, i.e. the sea water temperatures, had been filled in by a modification of harmonic inpainting (Kottler et al, 2016). For area 1, an interactive procedure for building outline correction using an OSM shapefile as supplementary input has additionally been performed.…”

Context-aware Patch-based Method for Façade Inpainting

“…The authors, however, decided to make use of context and to process not only the raw images from (Zhang et al, 2019), but also the classification results of fac ¸ade elements. In case of structure-based inpainting, (Kottler et al, 2016) demonstrated that even a simple method allows to preserve sharp edges between classes, once context information is taken into account. This paper will describe a suitable modification of the approach of (Criminisi et al, 2004).…”