Manipulation Detection in Satellite Images Using Deep Belief Networks

Satellite images are more accessible with the increase of commercial satellites being orbited. These images are used in a wide range of applications including agricultural management, meteorological prediction, damage assessment from natural disasters, and cartography. Image manipulation tools including both manual editing tools and automated techniques can be easily used to tamper and modify satellite imagery. One type of manipulation that we examine in this paper is the splice attack where a region from one image (or the same image) is inserted (spliced) into an image. In this paper, we present a one-class detection method based on deep belief networks (DBN) for splicing detection and localization without using any prior knowledge of the manipulations. We evaluate the performance of our approach and show that it provides good detection and localization accuracies in small forgeries compared to other approaches

EO-ALERT: NEXT GENERATION SATELLITE PROCESSING CHAIN FOR RAPID CIVIL ALERTS

In this paper, we provide an overview of the H2020 EU project EO-ALERT. The aim of EO-ALERT is to propose the definition and development of the next generation Earth observation (EO) data and processing chain, based on a novel flight segment architecture moving optimised key EO data processing elements from the ground segment to on-board the satellite. The objective is to address the need for increased throughput in EO data chain, delivering EO products to the end user with very low latency