时序特征图像配准算法的抗噪性分析

Analysis of noise resistance of time feature image registration algorithms

提出了一种基于时序特征变化的图像配准算法,通过时序灰度特征的分析和提取,实现了可见光与红外非固形动态目标图像的有效配准。重点分析了该算法的抗噪能力,当噪声对配准精度产生明显影响时,设计了一种预处理滤波方法,通过减小噪声项在时序特征提取中的影响,从而降低了算法的误配率。利用蜡烛火焰作为探测目标,通过实验表明,在图像信噪比为10 dB的情况下该算法的抗噪性较好,能够实现非固形目标的可见光与红外图像配准。当目标图像信噪比等于6 dB时,该算法就无法完成图像配准,此时采用预处理滤波方法,算法的误配率得以降低,能成功实现非固形目标的可见光与红外图像配准。实验中计算得到预处理方法的关键参数m取0.25时效果最好。

A temporal feature based image registration algorithm is proposed,which achieves effective registration of visible light and infrared non fixed dynamic target images through the analysis and extraction of temporal grayscale features.The focus was on analyzing the anti noise ability of the algorithm.When noise has a significant impact on registration accuracy,a preprocessing filtering method was designed to reduce the impact of noise on temporal feature extraction,thereby reducing the algorithm's mismatch rate.Using candle flames as the detection target,experiments have shown that the algorithm has good noise resistance at an image signal-to-noise ratio of 10 dB,and can achieve visible and infrared image registration of non fixed targets.When the signal-to-noise ratio of the target image is equal to 6 dB,the algorithm cannot complete image registration.In this case,the preprocessing filtering method is used to reduce the mismatch rate of the algorithm and successfully achieve visible and infrared image registration of non fixed targets.The key parameter of the preprocessing method calculated in the experiment is 0.25,which has the best effect.