改进梯度倒数加权滤波红外弱小目标背景抑制

Infrared dim and small target background suppression based on improved gradient inverse weighting filter

红外弱小目标易淹没在复杂的起伏背景中,为了提高后续目标的检测能力,往往需要通过抑制背景来增强目标信号。传统梯度倒数加权滤波对背景边缘缺乏稳健的适应性,本文提出了改进的梯度倒数加权滤波算法,即通过建立背景局部区域相关函数,利用背景局部统计特性自适应调整滤波参数,能较好地适应剧烈变化的背景,提高背景抑制能力。实验表明,改进的梯度倒数滤波器能对图像背景进行有效的抑制,总体性能优于其他背景抑制方法。

Dim and small infrared target easily flooded in complicated background. In order to improve the ability of target detection, the background is often suppressed to enhance the target signal. Referring to the lack of robust adaptability of the gradient inverse weighted filtering for background edges, an improved gradient inverse weighting filtering algorithm is proposed through the establishment of background local correlation function. The use of background local statistical characteristics of adaptive filter parameters, can better adapt to the drastic change in the background, and improve the ability to suppress background suppression algorithm. Experimental results show that the improved gradient inverse weighted filtering could effectively suppress the background of images, presenting a superior overall performance to other background suppression methods.