A New Operational Approach for Image Registration with High-Resolution SAR Data

Abstract:
For many image processing workflows, including change detection and data fusion, an accurate and automated image-to-image registration is a critical precondition. Particularly registering images with different modalities (e. g. Optical with SAR) is a known challenging problem. Therefore we developed the Hybrid Powered Auto-Registration Engine (HyPARE), combining all available spatial reference information with a number of image registration approaches to improve the accuracy, performance, and automation of tie point generation and image registration. For multisource data we implemented an optimized mutual information-based matching method, which produces more accurate results than traditional correlation-based measures. Moreover, we embedded the HyPARE algorithms in an IDL-based Task System – an important prerequisite for the operation in service-based production environments.