Abstract
Image registration is widely used in remote-sensing applications. The existing automatic image registration techniques fall into two categories: Intensity-based and feature-based; the latter (which extracts structures from both images) being more suitable for multi-sensor fusion, detection of temporal changes and image mosaicking. Conventional image registration algorithms have proven to be inaccurate, time-consuming, and unfeasible due to image complexity which makes it cumbersome or even impossible to discern the appropriate control points. In this study, we propose a novel method for automatic image registration based on topology (AIRTop) for change detection and multi‑sensor (airborne and spaceborne) fusion. In this algorithm, we first apply image‑processing methods (SURF—Speeded-Up Robust Features) to extract the landmark structures (roads and buildings) and convert them to a features (vector) map. The following stages are applied in GIS (Geographic Information System), where topology rules, which define the permissible spatial relationships between features, are defined. The relationships between features are established by weight-based topological map-matching algorithm (tMM). The suggested algorithm presents a robust method for image registration. The main focus in this study is on scale and image rotation, when the quality of the scanning system is constant. These seem to offer a good compromise between feature complexity and robustness to commonly occurring deformations. The skew and the anisotropic scaling are assumed to be second-order effects that are covered to some degree by the overall robustness of the sensor.
Highlights
Image registration is a critical pre-processing procedure in all remote-sensing applications that utilizes multiple image inputs, including multi-sensor image fusion, temporal change detection, and image mosaicking
This paper presents a novel method for automatic image registration based on topology rules (AIRTop) for change detection and multi-sensor fusion
The process continues at the local level using the second level of topology rules, where feature attributes are local connectivity and contiguity matrices, proximity matrix, heading matrix and Multiresolution Reeb Graph (MRG) parameters
Summary
Image registration is a critical pre-processing procedure in all remote-sensing applications that utilizes multiple image inputs, including multi-sensor image fusion, temporal change detection, and image mosaicking. As the significant regions (e.g., roofs) considered, and lines (e.g., roads), are expected to be stable in time at a fixed position, the feature-based method is more suitable for multi-sensor fusion, change detection and image mosaicking. The existing methods operate directly on gray intensity values and they are not suited for handling multi-sensor images. The search for discrete CPs can be divided into three main steps: (1) Selection of ―interesting points‖; (2) description of nearest points or features; (3) matching between images. This paper presents a novel method for automatic image registration based on topology rules (AIRTop) for change detection and multi-sensor (airborne and spaceborne) fusion
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