Infrared small target detection based on saliency and difference of Gaussian

Dong Li, Jie Yin, Guo-liang Zhou, Jianlin Huo, Jia-ying Li
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Abstract

The challenge of detecting the infrared small target in complex scenes is how to enhance the target area and suppress the interference of the background and noise. We present an infrared small target detection method based on saliency and difference of Gaussian. By calculating the spectral residuals of the original infrared images to obtain the saliency map, and a gray difference map is computed by adopting the difference of Gaussian. By normalizing and fusing these maps, the final feature response map is obtained, which can restrain the background noise and enhance the targets. Finally, the adaptive threshold segmentation method is used to detect small targets from the feature response map. Experimental result indicates that the proposed method achieves better image processing effect than traditional detection algorithm, works well under the interference of background and noise as well as detects the target accurately under different complex backgrounds.
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基于显著性和高斯差分的红外小目标检测
如何增强目标区域,抑制背景和噪声的干扰,是复杂场景下红外小目标检测面临的挑战。提出了一种基于高斯显著性和差分的红外小目标检测方法。通过计算原始红外图像的光谱残差得到显著性图,并采用高斯差分计算灰度差图。通过对这些映射进行归一化和融合,得到最终的特征响应映射,可以抑制背景噪声,增强目标。最后,采用自适应阈值分割方法从特征响应图中检测出小目标。实验结果表明,该方法比传统检测算法具有更好的图像处理效果,在背景和噪声的干扰下都能很好地检测出不同复杂背景下的目标。
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