Fast Retrieval Of Multi- And Hyperspectral Images Using Relevance Feedback

A high speed of retrieval is very important to developing an effective image cube search algorithm for the remote sensing community. Following the work of Berman and Shapiro, it is shown that a triangle inequality search technique applied to a relevance feedback retrieval algorithm can significantly speed up the search for and retrieval of physical events of interest in large remote-sensing databases. An improvement in retrieval speed is illustrated using hurricane queries applied to the multispectral GOES database.