1. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 1 INFORMATION MINING IN CATALOGS OF REMOTELY SENSED IMAGES

2. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 2 The need for catalogs of images  Images acquired by remote sensing satellites are : Numerous : after 16 years of operation, SPOT satellites have acquired more than 10 millions scenes all over the world Big : the size of a SPOT image ranges from 27 to 2150 Mbytes Diverse : Numerous sensors (optical and SAR) are available with different characteristics  Users (distributors, final users, …) need tools for browsing image archives in order to select those which fit their needs.

3. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 3 Current catalogs of images  Current tools are mainly based on the use of descriptive data, which are used as indexing data : Geographic location Sensor characteristics Viewing date Constraints expressing relationships with other data (stereoscopy, …) 2D index of some information which impacts the image use (snow, clouds, acquisition quality,...)...  The image content is displayed only as quick-look images together with the selected data ; its interpretation is left to the user.

4. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 4 Existing Catalogs Principle “Semantics” Localization Date & Time Sensor Image Archive Index Browse Engine Analysis and Visualization Tool Result Catalog Request

5. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 5 Some Catalogs Examples  SIRIUS Catalog for SPOT images Local : demodemo Internet : http://sirius.spotimage.fr/francais/Welcome.htmhttp://sirius.spotimage.fr/francais/Welcome.htm  Catalog of VEGETATION images Internet : http://cat.vgt.vito.be/login_french.htmlhttp://cat.vgt.vito.be/login_french.html ...

6. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 6 Present catalogs inefficiencies  Image content is not used Except through rough indexes on clouds, snow or technical quality  The interpretation of the results of queries is left to the user No assistance is provided to the user  The user’s interests are rarely taken into account A given request gives the same results whoever the user is  Catalogs are passive They could be more dynamic in order to propose images by themselves  Multi-sensors searches are difficult to achieve Catalog interoperability does not exist at image content level

7. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 7 Consequence of the inefficiencies  Remotely sensed data are not accessed enough

8. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 8 New generation of catalogs  Catalogs with a more dynamic behaviour : Exploit the content of the images for their selection Take the user’s interests into account Assist the user in the browsing process Attract the user through personalized proposals (subscription)...  The aim being to make the access to the relevant images easier, in order to increase their spreading and their use in applications.

9. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 9 Use of quick-looks content  The content of quick-look images can help answer only a limited number of questions : What are the changes which happened at the quick-look scale (macroscopic change detection) ? What are the resemblances between images based on macroscopic criteria (i.e. radiometry) ? Are there contextual phenomena which could prevent the exploitation of the full resolution image (clouds, snow, …) ? … ?

10. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 10 Resolution/Information trade-off  By definition a quick-look image does not contain all the information of the full resolution image. When a quick-look image is generated by a subsampling process (1:5 to 1:10), the information changes :  In a 1m resolution image, urban features are recognized  In a 10m resolution image, they are hardly seen In a commercial system, a free image must not contain this information.  In order to exploit a catalog of images by their content : Full resolution images must be used in order to access valuable information They must not be shown (free of charge)

11. CEOS - 13 may 2003 Alain Giros - Image Processing and Quality Division 11 The challenge of the full resolution images  There is a huge volume of data to manage : SPOT 1-4 :  10 Millions scenes  30 MegaBytes per scene »300 TeraBytes  It is thus impossible : To have all the full resolution images online To exploit them directly for each request  As a consequence : A digest of the image limited to the « just needed information » must be used during the processing of the queries. This information must be extracted on the fly just after the acquisition. SPOT5 :  2 Millions scenes  150 MegaBytes per scene »300 TeraBytes