Mutual Information (MI) is emerging as a very strong metric for image registration purposes in the literature. It has many applications from remote sensing to medical image registration. From this wide range of use of MI, images are mostly expressed in different numbers of bits (high dynamic range) especially in medical and satellite imaging. In such cases, contrast enhancement becomes inevitable before MI-based image registration since all the images should be in the same intensity range. The change in intensities in images will directly affect MI metric. Contrast enhancement methods also have a significant effect on the registration performance due to MI metric and this problem is not sufficiently addressed in the literature. In this paper, the effect of the outstanding contrast enhancement methods is examined on image registration performance. For this purpose, high dynamic range satellite images were used and Monte Carlo tests were performed. They are tried to be aligned with MI and constrained optimization by linear approximations (COBYLA) optimization algorithm. Consequently, it is found that contrast enhancement methods have an effect on MI-based image registration. It is concluded that Laplacian of Gaussian unsharp blending masks (LoGUnsarp), adaptive histogram equalization (AHE) and contrast limited adaptive histogram equalization (CLAHE) methods have better registration performance. They can be preferred in such registration purposes.
İbrahim Atlı, Ahmet Saraçoğlu, O. Serdar Gedik, "Contrast Enhancement Effect on High Dynamic Range Image Registration Using Mutual Information" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Visualization and Data Analysis, 2018, pp 355-1 - 355-6, https://doi.org/10.2352/ISSN.2470-1173.2018.01.VDA-355