首先基于红外物理基本理论建立目标光谱模型, 并利用图像时域及空域相关性建立多光谱背静抑制算法移除缓慢变化背景.通过实验统计方法将残差图像样本点特征概率分布近似为正态分布.基于此假设, 提出了一种新的基于目标辐射强度和光谱特征的联合检测方法.最后, 通过图像仿真和ROC曲线分析算法性能, 试验结果表明, 此方法能够在低信噪比情况下成功检测弱小点目标.

Target spectral signature is modeled firstly based on the thermal radiation theory and a multispectral background suppression approach is given. An experimentally justified assumption is made that the probability density functions (PDFs) of the feature vector can be modeled as Gaussian random process, and then a new unifying radiation intensity and radiation spectral signature (URIS) detector is developed. Finally, performance analyses based on a set of multispectral imagery and receiver operating characteristic (ROC) curves are presented. According to the experimental results, the URIS method can successfully detect dim point target in rather low signal-to-noise condition.