Network optimization and design in group-wise registration of terrain corrected satellite images

摘要

Direct web-based access to ready-to-use huge archives of satellite images and cloud-based services for planetary-scale data processing (e.g., Google Earth Engine or Amazon S3) is making possible to analyze unprecedented amounts of remotely sensed images simultaneously. Multiple images can be exploited to improve traditional results achieved through on-premises (on-site) processing, coupling cloud offerings, and redundant image information. This paper will introduce the concept of image network optimization for the case of registration problems based on groups of terrain-geocoded images. The particular case of multi-image registration will be discussed, notwithstanding the proposed approach can be extended to other practical issues, as illustrated in the paper. The concept of network design and optimization for satellite images is mathematically formulated and quantified with a multi-purpose objective function comprising precision, reliability, and cost. Results are illustrated with theory and numerical simulations carried out with a rigorous stochastic approach, in which the significance of the different input variables is estimated. The developed network-based approach allows one to reduce the number of external constraints, mainly focusing only on images and their increasing availability through web-services integrated by massive cloud computation capability.