TOWARDS AN AUTOMATIC INTERPRETATION AND KNOWLEDGE BASED SEARCH OF SATELLITE IMAGES IN DATABASES

摘要

This paper shows a prototype automatic interpretation system for ocean AVHRR (Advanced Very High Resolution Radiometer) satellite images. It is built on a three-level knowledge model (pixel, regional and domain semantic problem levels) and uses several connectionist computational approaches. First, artificial neural net models (to the pixel level) were used for basic preprocessing tasks such as cloud masking. Next, a new connectionist technique using input vectors with nonnumerical regional marine features has also been developed and used in the identification phase. The paper shows some results of oceanic structure identification tasks (wakes, upwellings and eddies) in infrared images of the NW African coast and Canary Islands. These results illustrate a procedure for improving automatic oceanic interpretation of satellite images.