基于视觉对比度机制的红外弱小目标检测算法

Infrared small target detection algorithm using visual contrast mechanism

针对红外图像中空天、海天等复杂背景及像素点噪声容易造成检测虚警的问题,提出一种基于视觉对比度机制的红外弱小目标检测算法。首先,通过新定义的局部对比度算子获取对比度增强的图像,该步骤可抑制背景杂波与像素点噪声对检测的干扰,提高图像的信杂比,增强目标区域的视觉显著性。然后,利用多尺度方法优化图像的显著区域,以增强算法的适用性,从而实现算法对不同尺寸的弱小目标的有效检测。最后,利用自适应阈值分割方法获取待检测的真实目标。实验结果表明,该算法无需图像预处理环节即可实现对不同尺寸的弱小目标的鲁棒性检测,对比常用算法具有快速性、高效性和较强的适用性。

Aiming to resolve the problem that the complex background of sea-sky and also pixel-level noise are easy to result in false alarm in the process of target detection,a detection algorithm of the infrared weak target using visual contrast mechanism is proposed.First,a contrast-enhanced image is obtained by using the defined local contrast measure operator.This step can enhance the visual saliency of the target region,and simultaneously suppress the interference of the complex background and pixel-level noise,so as to improve the signal-to-clutter ratio (SCR) of the image.Then,the saliency region of the image is optimized in multi-scale to improve the versatility of the algorithm,so that it can be competent in the detection of weak targets of different sizes.Finally,an adaptive threshold segmentation is used to obtain the real target.The experimental results show that the proposed algorithm can realize the robustness detection of different sized weak targets without image preprocessing.Thus it is an effective method for infrared weak target detection compared with other algorithms with its high rapidity,efficiency and strong applicability.