Infrared small-target detection plays an important role in image processing for infrared remote sensing. In this paper, we formulate this problem as salient region detection, which is inspired by the fact that a small target can often attract attention of human eyes in infrared images. We show that the convolution of the image amplitude spectrum with a low pass Gaussian kernel of an appropriate scale is equivalent to an image saliency detector. In this paper, we present a quaternion representation of an image which is composed of its intensity after denoising, the horizontal gradient and the vertical gradient. Therefore, a new method for infrared small target based on hyper complex Fourier transform (HFT) is proposed. The saliency map is obtained by reconstructing the 2D signal using the original phase and the amplitude spectrum, filtered at an appropriate scale. Experimental results demonstrate that the proposed algorithm is able to predict salient regions on which people focus their attention.
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