Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Baltsavias, Emmanuel P.

Bibliographic data

Monograph

Persistent identifier:: 856473650

Author:: Baltsavias, Emmanuel P.

Title:: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Sub title:: Joint ISPRS/EARSeL Workshop ; 3 - 4 June 1999, Valladolid, Spain

Scope:: III, 209 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856473650

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: TECHNICAL SESSION 2 PREREQUISITES FOR FUSION / INTEGRATION: IMAGE TO IMAGE / MAP REGISTRATION

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: AUTOMATED PROCEDURES FOR MULTISENSOR REGISTRATION AND ORTHORECTIFICATION OF SATELLITE IMAGES. Ian Dowman and Paul Dare

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 from the images and unwanted information is removed before processing takes place. This method gives root mean square errors in the order of 1 - 2 pixels for the Istres data. Tests were carried out with various edge detectors with little variation shown to the final results. Between 1000 and 1700 points were extracted from the Istres scene. The Sobel operator was the most convenient because it is the only one tested which gives both the edge location and edge strength which is needed for the dynamic programming algorithm. The points extracted were used to refine the registration and better results were obtained. Figure 8. Matched patches from SAR and SPOT images. 6. AUTOMATIC REGISTRATION OF FULL SCENE IMAGES The tests described above have been carried out on small scenes of about 500 x 500 pixels. These have been chosen to include a number of suitable features for matching and to be flat areas so that relief distortion does not need to be taken into account. In order to demonstrate that the method is more widely applicable, a test was carried out on registration of full SAR and SPOT scenes. The area used was the same as the one for the subscenes. The technique of using image pyramids was tested but found to give rather poor results. An alternative method is proposed which is based on using image tiles. The full scene images are approximately aligned using either ephemeris data, or with 3 or 4 manually selected tie points and then split into tiles. The tiles can be selected automatically to give a full distribution over the image, or they can be selected manually to ensure that tiles with good features for matching are chosen. Each selected tile is processed in the manner described above using patch matching and edge matching and the tie points which are generated are used to transform the whole scene. The method was tested on the SAR and SPOT scenes of SW France. Manually tie pointing gave a good initial registration. Twelve 512 x 512 tiles were selected for the refined registration. Of the 12 ten produced correctly matched patches and these resulted in 39 matches across the whole image. These were used to register the images using an affine transformation with a resultant root mean square error of 16 pixels and 13 pixels derived from two sets of tie points split between control points and check points and then reversed. The error was much greater in the x direction than in the y direction, probably reflecting the inadequacy of the affine transformation for this operation. The tie points were nearly all located on water features and most points had an elevation of less than 50m. Edge matching was used to refine the matching. 3488 tie points were generated and the root mean square errors on the two groups of tie points were 11 pixels in both cases. This is clearly an improvement but the larger residuals in the x direction remain. The test has clearly shown that near automatic registration of whole scene images is possible using the techniques described in this paper. Since the paper is mainly concerned with techniques for tie point generation, no attention has been paid to selecting the most suitable model for transformation when two different types of image are used. Selection of a suitable model will clearly improve the results of the registration. 7. CONCLUSIONS The work described in this paper has indicated that registration of data of different types is possible using automatic extraction and matching of polygons and that edge matching can be used to refine the process. The ARCHANGEL project, which is not discussed in detail here, has shown what can be done with images and vector data and results are presented which demonstrate the potential of this method. Similar techniques for patch extraction from images have been discussed in the context of matching SAR and SPOT data and have been shown to be effective both on subscenes and on full scene images. Data of only one area has been used but experience suggest that the requirement for only a few well distributed points over a scene should be possible in many areas and conditions in the world. This work has been done by the second author towards his PhD thesis (Dare, 1999) and he has identified many improvements which could be made to the methods discussed in the paper and also additional techniques which could be used. As regards the completion of an accurate end-to-end system, the most important of these is probably the use of a suitable transformation model. If a DEM is available, then geocoding of both images would be possible using the initial ephemeris of ERS for example to establish a reference system and then to register the SPOT data to the geocoded SAR data. Renouard and Perlant (1993) have described the basics of such a method. Alternatively, the ARCHANGEL method could be used, if maps and a DEM are available. ACKNOWLEDGEMENTS The work on ARCHANGEL was carried out as an EC Fourth Framework project Environment and Climate Programme, Theme 3 Grant No. ENV-CT96-0306 (DG12-DTEE). The work on registration of SAR and SPOT was carried out as a PhD project supported by NERC, Grant No. GT4/95/207D. SAR data was provided by ESA, and SPOT data was provided by SPOT Image for an OEEPE project on Aerial Triangulation of SPOT data.

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