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Abstract. Image compositing is defined as the assembling of two or more overlapping images into a single image. Recently, a morphological image compositing algorithm was proposed that automatically positions seam lines along salient image structures. This algorithm requires that all images used in the compositing procedure be held in computer memory. Hence, when composing large images such as satellite imagery acquired over a large region, the maximal capacity of random access memory of 32 bit computers is rapidly exceeded. In this paper, we present a parallel algorithm producing the same results whilst requiring only one input image at a time to be held in memory. The algorithm is illustrated for the automatic production of pan-European mosaics of Landsat images.

The goal of the two year Ground European Network for Earth Science Interoperations-Digital Repositories (GENESI-DR) project was to build an open and seamless access service to Earth science digital repositories for European and world-wide science users. In order to showcase GENESI-DR, one of the developed technology demonstrators focused on fast search, discovery, and access to remotely sensed imagery in the context of post-disaster building damage assessment. This paper describes the scenario and implementation details of the technology demonstrator, which was developed to support post-disaster damage assessment analyst activities. Once a disaster alert has been issued, response time is critical to providing relevant damage information to analysts and/or stakeholders. The presented technology demonstrator validates the GENESI-DR project data search, discovery and security infrastructure and integrates the rapid urban area mapping and the near real-time orthorectification web processing services to support a post-disaster damage needs assessment analysis scenario. It also demonstrates how the GENESI-DR SOA can be linked to web processing services that access grid computing resources for fast image processing and use secure communication to ensure confidentiality of information.Remote Sens. 2011, 3 1235

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