Researchers working on the project report that the wavelet technique decreases the number of undetected mines by at least 50 percent. Statistical classification, combined with wavelet-based filtering dramatically decreases the number of false alarms. We expect to see further improvement once the technologies are integrated into a single system. In side scan sonar images, mines appear as tiny bright objects with telltale dark shadows. Wavelet analysis cleans up the images by isolating and discarding the small features that may interfere with seeing mines.
Wavelets are also good at representing images parsimoniously, with very few bits of information.
The technology can reduce some megabyte images to 1,000 bytes, so there is much less data to look through to find the mines. Next, statistical analysis of the data makes very sophisticated judgments that reveal the mines and pinpoints them on the electronic images. Reducing the number of false alarms is a tremendous time saver given the current slow methods of deactivating mines. Eventually, advances in robotics technology will make autonomous remote deactivation possible, Dr. Lau predicted. The Office of Naval Research pursues an integrated science and technology program from basic research through manufacturing technologies.