Performance Evaluation of Quadratic Correlation Filters for Target Detection and Discrimination in Infrared Imagery

摘要

The detection and discrimination of targets in infrared imagery has been a challenging problem due to the variability of the target and clutter (background) signatures. In this paper we discuss the application of a novel quadratic filtering method using missile seeker infrared closing sequences. Image filtering techniques are well suited for target detection applications since they avoid the disadvantages of typical pixel-based detection schemes (such as segmentation and edge extraction). Another advantage is that the throughput complexity of the filtering approach, in the detection process, also does not vary with scene content. The performance of the proposed approach is assessed on several data sets, and the results are compared with that of previous linear filtering techniques. Since we can obtain the signature of some of the clutter "in-the-field" or during operation, we examine the impact of updating the filters to adapt to the clutter.