由于探测器本身固有的特性以及**上的极限使用要求，红外图像普遍存在目标－背景间对比度较差、目标边缘模糊和噪声较大等特点，采用常规模板匹配、Hu矩方法难以取得理想的检测效果。针对低信噪比红外目标图像，分析了伪Zernike矩的基本原理、不变性和计算方法，提出了低信噪比红外目标检测的伪Zernike矩方法，并比较了模板匹配、Hu矩、伪Zernike矩方法的目标检测效果。理论分析和实验验证了该方法的有效性。

As inherent characters in infrared detectors and utmost military application demands,low-SNR infrared images often present bad features such as low target-background contrast,blurred edges and large noises,so traditional target recognition methods as template matching or Hu moments cannot detect target effectively. Aimed at low-SNR infrared images,the principle,invariant property and computational methods of Pseudo-Zernike moments are analyzed,and a method for low-SNR infrared target detection based on Pseudo-Zernike moments is proposed. Target recognition effects among template matching,Hu moments and Pseudo-Zernike moments are compared via experiments. Theoretical analysis and experiment results show that the proposed method is effective for low-SNR infrared target detection.