双机IRST配准融合图像的弱小目标检测方法

针对单机红外搜索跟踪（IRST）系统探测距离和精度有限，得到的红外图像在杂乱背景和强噪声环境中弱小目标难以检测的问题，采用双机IRST对同时刻同目标区域探测后的图像进行配准融合，融合过程中采用高频基于区域、低频基于像素的多规则算法，提出一种基于小波变换与边缘信息表征的目标检测方法。仿真实验表明，多规则融合算法使图像质量评价指标提高了30%～50%，该目标检测方法可有效剔除虚假目标及滤除杂波干扰，从融合滤波前的7个减少到3个，虚警率降低，有助于弱小目标更为精确的检测识别。

Small target detecting method using dual-craft IRST image matching and fusion

Aiming at the problem that the small target was hard to be detected from infrared image in single craft-s infrared search and track (IRST) system under disorder background and great yawp situation, due to the limit of detecting distance and precision, the dual-craft coordinated detecting of the same target area at the same time was used. Then the process of images matching and fusion was conducted, in which a multi-rule algorithm that the high frequency based on area and the low based on pixel was adopted, and a target detecting method based on wavelet transform and edge information token was proposed after the fusion. The emulation experiment shows that the multi-rule fusion algorithm can improve the evaluation index of images quality by from 30% to 50%, and the method can eliminate false targets from 7 to 3，filter disturbing waves, reduce the false alarm rate and detect small targets efficiently and accurately.