人工智能
灰度
计算机视觉
计算机科学
仿射变换
图像配准
模式识别(心理学)
特征(语言学)
转化(遗传学)
数学
图像(数学)
哲学
基因
化学
纯数学
生物化学
语言学
作者
Xu Chen,Lei Liu,Jingzhi Zhang,Wenbo Shao
标识
DOI:10.1016/j.infrared.2020.103549
摘要
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.
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