AUG Signals has developed unique target classification and identification technologies. Used in conjunction with our innovative detection algorithms, these have been applied to a variety of applications, from vessel and military targets identification to waterborne contaminants identification and mineral/oil signature identification.
An example of hyperspectral military targets identification is provided below.
Figure 1 is the 6th band image generated using hyperspectral sensor Probe-1. There are eight different military targets in the scene. The ground truth is provided in Figure 2 where targets are marked by different colors and symbols.
The state-of-the-art spectral analysis technology, as well as AUG Signals technology are applied to identify these targets. The results are provided in Figures 3 and 4, respectively.
Figure 3. Identification result using state-of-the-art spectral analysis technology.
Figure 4. Identification result using technology developed by AUG Signals.
As can be seen in Figure 3, there are many non-target pixels miss-detected as targets. In addition, most of the detected targets are miss-identified into wrong categories of targets. The result generated using our technology is much clearer. All the targets are correctly identified with only few false alarms. In this example, the performance using our technology is 10 times more accurate than the state-of-the-art technology.
In addition to military applications, AUG’s hyperspectral detection and identification technologies are used to generate state-of-the-art mineral maps. AUG Signals’ algorithms allow for unmatched mapping speed and accuracy; mapping of vast areas that used to take up to 5 years to complete can now be accomplished in a matter of hours, with the end-result being significantly more accurate (resolution < 1m2 vs. 2km2).
The following is an example of mineral maps obtained using AUG Signals’ spectral signal processing techniques. The image cube is Probe-1 data obtained in southern Baffin Island. Some preprocessing of the data have been performed (preprocessing includes calibration, atmospheric correction, water and snow masking, etc). Figure 5 is a spatial subset of the original RGB image (Gaussain enhancement applied) of Probe-1 data obtained in Buffin Island. Spectral signatures of seven materials are plotted in Figure 6. Those seven materials of interest are presented in the image scene in a mixed form. AUG Signals’ confidence images of the first three materials are presented in Figure 7 as RGB images. Figure 8 is a classified image of all 7 materials where each color represents a classified material.
The feature-based classifier has been successfully applied to Radarsat-2 data (with 3 meters resolution) with very high classification accuracy (approximately 0.96). In the testing data, 4 vessel classes were present: CFAV Quest, CCGS Sir Wilfred Grenfell, CCGC Sambro, and Divecom III, with dimensions of 76m x 12.6m, 64.48m x 5.18m, 16.25m x 5.18m, and 13.3m x 4.45m, respectively.
AUG Signals has developed a robust vessel classification system based on polarimetric decomposition and transformation by integrating the company’s advanced CFAR detection algorithm into the polarimetric decomposition classification method, thereby increasing the classification and identification accuracy.
To utilize polarimetric-based vessel classifier, data should have full polarizations to apply polarimetric decomposition and transformation.