Monomodal Image Registration by Tensor Analysis: Going Beyond the Brightness Constancy Assumption

There is a great number of image applications, where the first step in the analysis is to associate the same point in two or more images that were taken from different viewpoints or at different times. This procedure is called image registration (IR). This work proposes a new efficient method for IR based on tensor calculus that overtakes the usual assumption of brightness consistency among the involved images. The main idea is to define transformations in serial images by using tensor behavior on coordinate transformations. It combines the simplicity and efficiency of the computer implementation with the correctness and elegance of the physic foundations. Moreover, it introduces a complete different way for management of this very important application of image processing: the use of the principal axis idea. The significant advantage of the proposed method is its promptitude and robustness for use in medical images in a way the as far as we known have never considered before. Experimental results in real examinations demonstrate that the proposed algorithm is highly accurate and outperforms a combination of the most updated IR approaches.