Name
Abstract | ||
|---|---|---|
The automatic registration of image pairs composed of optical and synthetic aperture radar (SAR) images is a highly challenging task because of the inherently different physical, statistical, and textural properties of the input data. Information-theoretic measures capable of comparing local intensity distributions are often used for multisensor optical-SAR registration. Moreover, the growing availability of such heterogeneous data from current space missions require multisensor registration methods able to run on large-scale datasets with acceptable computation times. In this paper, a novel method is proposed combining information-theoretic area-based registration with a sequential image tiling strategy. Experiments with optical-SAR data collected by a variety of sensors (Sentinel, Landsat, ERS, etc.) suggest both qualitatively and quantitatively the effectiveness of the proposed strategy in achieving accurate registration with low computational cost. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/IGARSS46834.2022.9884048 | IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium |
Keywords | DocType | ISSN |
Image registration,multisensor data,optical,synthetic aperture radar (SAR),tiling,large scale | Conference | 2153-6996 |
ISBN | Citations | PageRank |
978-1-6654-2793-7 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Solarna | 1 | 0 | 0.34 |
| Luca Maggiolo | 2 | 0 | 0.34 |
| Gabriele Moser | 3 | 919 | 76.92 |
| Sebastiano B. Serpico | 4 | 749 | 64.86 |