Abstract For the past few decades, due to the extensive application of multi-sensor vision systems, the technology of multimodal image registration has been continuously developed, especially the registration of infrared and visible images. However, due to the difference of grayscale distribution, the results of most existing methods for infrared and visible image registration are commonly not satisfactory. Therefore, this paper proposes a method for visible and infrared image registration using edge features and partial intensity invariant feature descriptors (PIIFD) with scale invariance. This method extracts conspicuous edge features of the source image pair through a window grayscale weight algorithm, and calculates the feature descriptions of the edge images with scale invariant PIIFD. And then Gaussian field estimator and affine transform are used to realize image feature matching and alignment transformation. The quality and quantity comparisons with 5 other most advanced methods reveal that our method can attain an ascendant performance, can accurately and efficiently realize the registration of infrared and visible images.

中文翻译：

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具有边缘特征和尺度不变 PIIFD 的多模态图像配准

摘要 几十年来，由于多传感器视觉系统的广泛应用，多模态图像配准技术得到不断发展，尤其是红外和可见光图像的配准。然而，由于灰度分布的差异，现有的大多数红外和可见光图像配准方法的结果普遍不令人满意。因此，本文提出了一种使用边缘特征和具有尺度不变性的局部强度不变特征描述符（PIIFD）进行可见光和红外图像配准的方法。该方法通过窗口灰度权重算法提取源图像对的显着边缘特征，并计算具有尺度不变PIIFD的边缘图像的特征描述。然后利用高斯场估计和仿射变换实现图像特征匹配和对齐变换。与其他5种最先进方法的质量和数量比较表明，我们的方法可以取得优势，可以准确高效地实现红外和可见光图像的配准。