Mutual information has many applications in image alignment and matching, mainly due to its ability to measure the statistical dependence between two images, even if the two images are from different modalities (e.g., CT and MRI). It considers not only the pixel intensities of the images but also the spatial relationships between the pixels. In this project, we apply the mutual information formula to image matching, where image A is the moving object and image B is the target object and calculate the mutual information between them to evaluate the similarity between the images. For comparison, we also used entropy and information-gain methods to test the dependency of the images. We also investigated the effect of different environments on the mutual information of the same image and used experiments and plots to demonstrate.

翻译：互信息在图像配准与匹配中具有广泛应用，这主要归功于其能够度量两幅图像之间的统计依赖性，即使这两幅图像来自不同模态（例如CT与MRI）。它不仅考虑图像的像素强度，还考虑像素间的空间关系。在本项目中，我们将互信息公式应用于图像匹配，其中图像A为运动物体，图像B为目标物体，并计算二者之间的互信息以评估图像的相似性。作为对比，我们还使用了熵与信息增益方法来测试图像的依赖性。此外，我们探究了不同环境对同一图像互信息的影响，并通过实验与图表进行了验证。