Automatic registration of multi-source medium resolution satellite data

Abstract

ABSTRACT:Multi-temporal and multi-source images gathered from satellite platforms are nowadays a fundamental source of information in several domains. One of the main challenges in the fusion of different data sets consists in the registration issue, i.e., the integration into the same framework of images collected with different spatial resolution and acquisition geometry. This paper presents a novel methodology to accomplish this task on the basis of a method that stands out from existing approaches. The whole data (time series) set is simultaneously co-registered with a two-dimensional multiple Least Squares adjustment with different geometric transformations implemented. Some tests were carried out with different geometric transformation models (including similarity, affine, and polynomial) and variable matching thresholds. They showed a sub-pixel precision after the computation of multiple adjustment. The use of multi-image corresponding points allowed the improvement of the registration accuracy and reliability of a time series made up of data imaged with different sensors.

A Systematic Solution to Multi-Instrument Coregistration of High-Resolution Planetary Images to an Orthorectified Baseline

“…Despite the significant effort that has been put into the automation of remote sensing image coregistration, there are still many applications where the coregistration process is done manually, i.e., through some specialized software [27] that allows the user full control of the coregistration pipeline. However, manual coregistration is a tedious task that requires human resources, cannot be employed for batch-mode processing to coregister large volumes of input data, and, last but not least, it may lead to inaccurate tie-points when coregistering multisource images [28], [29].…”