AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY
This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-04-01
|
| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/83/2018/isprs-annals-IV-3-83-2018.pdf |
| _version_ | 1818020166204653568 |
|---|---|
| author | P. Fischer P. Schuegraf N. Merkle T. Storch |
| author_facet | P. Fischer P. Schuegraf N. Merkle T. Storch |
| author_sort | P. Fischer |
| collection | DOAJ |
| description | This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way. |
| first_indexed | 2024-04-14T08:02:19Z |
| format | Article |
| id | doaj.art-a54174bc9c734e71b930de27010a7a29 |
| institution | Directory Open Access Journal |
| issn | 2194-9042 2194-9050 |
| language | English |
| last_indexed | 2024-04-14T08:02:19Z |
| publishDate | 2018-04-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-a54174bc9c734e71b930de27010a7a292022-12-22T02:04:52ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502018-04-01IV-3839010.5194/isprs-annals-IV-3-83-2018AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERYP. Fischer0P. Schuegraf1N. Merkle2T. Storch3Remote Sensing Technology Institute, German Aerospace Center (DLR), M¨unchener Str. 20, 82234 Wessling, GermanyDept. of Scientific Computing, University of Applied Science Munich, Lothstr. 20, Munich, GermanyRemote Sensing Technology Institute, German Aerospace Center (DLR), M¨unchener Str. 20, 82234 Wessling, GermanyRemote Sensing Technology Institute, German Aerospace Center (DLR), M¨unchener Str. 20, 82234 Wessling, GermanyThis paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/83/2018/isprs-annals-IV-3-83-2018.pdf |
| spellingShingle | P. Fischer P. Schuegraf N. Merkle T. Storch AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY |
| title_full | AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY |
| title_fullStr | AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY |
| title_full_unstemmed | AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY |
| title_short | AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY |
| title_sort | evolutionary algorithm for fast intensity based image matching between optical and sar satellite imagery |
| url | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/83/2018/isprs-annals-IV-3-83-2018.pdf |
| work_keys_str_mv | AT pfischer anevolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT pschuegraf anevolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT nmerkle anevolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT tstorch anevolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT pfischer evolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT pschuegraf evolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT nmerkle evolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery AT tstorch evolutionaryalgorithmforfastintensitybasedimagematchingbetweenopticalandsarsatelliteimagery |