  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.
