Infrared and visible light image registration algorithm based on clustering and mutual information

Image registration has always been the hot topic in image research field, and the mutual information registration method has become a commonly used method in image registration because of its high precision and good robustness. Unfortunately, it has a problem for infrared and visible image registration. Lots of rich background detail information is usually provided by the visible light band, while the infrared image can locate an object (heat source) with a higher temperature, and often can't obtain the background information. The large difference in the background information of the two images not only interferes with the accuracy of the registration algorithm but also brings a lot of computation. In this paper, a method of fuzzy c-means clustering is used to separate foreground and background which reduces the background information interference for registration, based on the feature that the infrared image and the visible image have a high uniformity in the target area and a large difference in the background area. Then, the mutual information of the foreground image marked by clustering algorithm is calculated as the similarity measure to achieve the purpose of registration. Finally, the algorithm is tested by the infrared and visible images acquired actually. The results show that the two image s registration is perfectly implemented and verify the effectiveness of this method.