Structural Representation: Reducing Multi-Modal Image Registration to Mono-Modal Problem

Keyvan Kasiri, David Clausi, Paul Fieguth
2015 Vision Letters  
<p>Registration of multi-modal images has been a challenging task<br />due to the complex intensity relationship between images. The<br />standard multi-modal approach tends to use sophisticated similarity<br />measures, such as mutual information, to assess the accuracy<br />of the alignment. Employing such measures imply the increase in<br />the computational time and complexity, and makes it highly difficult<br />for the optimization process to converge. The presented registration<br
more » ... stration<br />method works based on structural representations of images<br />captured from different modalities, in order to convert the multimodal<br />problem into a mono-modal one. Two different representation<br />methods are presented. One is based on a combination of<br />phase congruency and gradient information of the input images,<br />and the other utilizes a modified version of entropy images in a<br />patch-based manner. Sample results are illustrated based on experiments<br />performed on brain images from different modalities.</p>
doi:10.15353/vsnl.v1i1.60 fatcat:qzx32b446verhgyf76muo4p67u