Detection of small target in infrared image sequences using attention mechanism

The requirement of algorithm for detecting small target in infrared image sequences is not only a high rate to identify the true target and a low false alarm rate, but also the computation efficiency. By employing the selective attention mechanism, biological visual system can interpret a complex incoming image in real time with limited hardware resources. Much evidence has suggested that the biological visual system processes information in a serial strategy which rapidly selects a small relevant region in scene for further complex and time consuming analysis. In this paper, a two component computation scheme is proposed to detect dim targets in infrared image sequences. In the first process stage, an efficient method is applied to extract the potential targets which are further identified in second phase, the true targets are detected, and the spurious objects are rejected. The attention-based approach reduces the computation complexity, while the other performance aspects are not traded off. Experimental results indicate that the proposed extraction and recognition modules exhibit excellent performance of detecting small target in infrared image sequences, especially in process speed aspect