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 AUTOMATED PROCEDURES FOR MULTISENSOR REGISTRATION AND ORTHORECTIFICATION OF SATELLITE IMAGES Ian Dowman* and Paul Daret ♦Department of Geomatic Engineering, University College London, Gower Street, London WC1E 6BT, idowman@ge.ucl.ac.uk ■¡■Formerly at UCL now at Department of Geomatics, University of Melbourne, Parkville, Victoria 3052, Australia KEY WORDS: Automated registration, satellite data, image segmentation, polygon matching. ABSTRACT The need for automation in the registration of image to image and image to map is widely recognised and work has been going on for some time in both the photogrammetric and remote sensing disciplines. The image to image registration problem is some way to being solved for images from the same or similar sensors but there are considerable problems if the resolution of the images are different or if optical and microwave sensors are involved. Strategies are needed which will identify common features in images with different pixel size or radiometry and without dependency on initial orientation. The basic techniques which are used are the extraction of line and area features from image and/or a map and then the matching of these features. The polygon or patch is the main feature used. These are extracted from vector data by selecting features with an appropriate attribute, for example lakes, forests or field boundaries. The polygons can be extracted from the images by thresholding, homogeneous patch detection or segmentation. The paper describes studies to determine the best method for patch extraction for an automatic system to match SAR and SPOT data and some new techniques for this extraction, including techniques for increasing automation. The basic techniques of matching polygons is adapted from Abbasi-Dezfouli and Freeman, (1994). Polygons are characterised by a number of parameters such as shape and area. A revised approach is described here which does not use chain code and in which an iterative approach is followed. Other developments from previous methods are also described and results show that registration of complete satellite images can be achieved. Results from the image to map registration in the ARCHANGEL project are also described. 1. INTRODUCTION The term automated needs some clarification. The ultimate aim of any digital system will often be to complete a process from end to end without human interference. Such an aim cannot be met at present and will not be met within the near future for registration of images. However, human interaction can be minimised and rationalised at a number of levels. We can make individual algorithms or processes as automatic as possible and only require human intervention to set parameters and check output. We can also design strategies in such a way that some decisions can be automatically taken, or at least set at the beginning of the procedure. Both these aspects will be discussed in the paper. The paper will first review the requirements for image to image registration and image to map registration, and set out the overall strategies which have been adopted. The algorithms to be used to extract features for matching will then be described and choice of suitable algorithms discussed. The selected algorithms will then be applied to polygon extraction and techniques for this process will be described and discussed. The techniques for polygon matching will then be presented and finally some examples will be given. 2. STRATEGIES FOR IMAGE REGISTRATION An image registration system needs to be as generic as possible and we have worked towards a system which will accept any type of image data as input. This includes data from optical sensors, from microwave sensors and from vector data bases (maps). There are differences in the types of feature which can be extracted from data of different scale or resolution. Here, we will concentrate on small scale data such as might be collected from satellite sensors and be compatible with map scales of 1:10 000 to 1:50 000. Such an approach implies the setting of an overall strategy and the provision of a toolbox of processes to meet different requirements. The high level strategy is shown in Figure 1. Figure 1. A registration strategy. Polygonal features are chosen as the prime feature for matching because such features are found in all types of data. Obvious examples are water bodies, forests and field boundaries. These features can be found by segmenting images or will be extracted

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