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Infrared target detection in large field of view using visual attention

High-resolution, multi-pixels and large field of view (FOV) infrared (IR) detector is an important research direction, which greatly improves the target detection capability. This paper addresses the infrared target detection under the guidance of attention mechanism. The Gabor filter is used to extract the elementary visual feature of infrared image for its orientation selectiveness. Then it researches the reasons that produce visual saliency in frequency domain, and provides the multichannel feature combination strategy to generate the feature map. Further, a novel saliency detection model using Fourier spectrum filtering, is presented to calculate feature regions of infrared image. Experimental results using a wide range of real IR images demonstrate that the proposed algorithm is robust and effective, yielding satisfying results for infrared target detection in large FOV with complex background and low SNR.