基于互补梯度增强的红外线列扫描图像小目标检测

Small Target Detection of Infrared Linear Array Image Based on Complemented Gradient Enhancement

针对红外弱小目标难以识别、存在虚警的问题,根据红外线列探测器的噪声特性与小目标的梯度对称性,提出一种通过在图像梯度空间下构建多尺度堆叠增强重积分图(MSERI)来检测红外小目标的方法。估计不同的小目标尺寸,从多个方向计算图像的单向梯度图,利用估计尺寸寻找单向梯度图中各梯度值的互补梯度,对图像进行增强,之后对增强后的单向梯度图进行积分以还原图像并堆叠不同方向的积分图像,综合不同估计尺寸的堆叠图以获得增强结果。最后根据增强结果中的图像像素邻域的杂波峰-峰值计算自适应调节阈值,分割得到红外小目标。实验表明,所提方法在多种场景下均具有较好的检测能力与较低的虚警率,且运行速度优于其他性能类似的算法。

Aiming at the problem that the detection of weak and small infrared targets could be affected by false alarm,according to the noise characteristics of infrared line array sensor and the gradient symmetry of small target,a method of constructing multi-scale stacked enhanced re-integrated image(MSERI)in image gradient space is proposed to detect small infrared target.First,different sizes of small targets are estimated,and the unidirectional gradient images of the original image are calculated from multiple directions.Then,the complementary gradient of the gradient values in the unidirectional gradient image are found to enhance the gradient image.Then,the enhanced gradient image is integrated to restore the image,and the integrated images in different directions are stacked as a image.And,the maximum enhanced value is taken from the stacked images with different estimated sizes as the enhanced result.Finally,according to the peak to peak value of clutter in the neighborhood of pixels from enhanced result,the adaptive threshold is calculated to segment small infrared targets.The experimental results show that the method has better detection ability and lower false alarm rate in various scenarios,and the running speed is better than algorithms with similar performance.