Tensor-based descriptor for image registration via unsupervised network
Qiegen Liu, HENRY K. LEUNG · 2017
Since the significant intensity variations existed between different modal images, the deformable registration is still very challenging. In this paper, in order to alleviate the variations deficiency and attain robust alignment, we propose a multi-dimensional tensor based modality independent neighbourhood descriptor (tMIND) to measure the similarity between the images. The tMIND compares the neighboring tensors which consisting of multi-filters induced features. In this work we learn these filters via PCA network (PCANet). We additionally describe the scheme of incorporating these filters into the tMIND. Experimental evaluations demonstrate its promise and effectiveness over the current state-of-the-art approaches.