Fast Detection of Distant, Infrared Targets in a Single Image Using Multiorder Directional Derivatives

Abstract

The fast and robust detection of far targets is one of the key techniques in infrared searching and tracking applications. Using multiorder directional derivatives, an effective and concise detection method performed on a single IR image is proposed in this article. First, multiorder directional derivatives of an image are derived from the facet model. According to the derivative characteristics of small targets, enhancement filters are designed to maximize the target components. Convolved with these filters, the small targets are enhanced and the backgrounds are suppressed in each derivative subband. The final result is obtained by fusing all these filtered derivative subbands. The experimental results demonstrate that the proposed method consistently achieves a robust and effective performance on all datasets. In addition, the low computational complexity makes the proposed method suitable for real time detection purpose.