Enforcing stochastic inverse consistency in non-rigid image registration and matching

Sai-Kit Yeung, Chi-Keung Tang, Pengcheng Shi, Josien P.W. Pluim, Max A. Viergever, Albert C.S. Chung, Helen C. Shen
2008 2008 IEEE Conference on Computer Vision and Pattern Recognition  
This paper presents a new method to enforce inverse consistency in nonrigid image registration and matching. Conventional approaches assume diffeomorphic transformation, implicitly or explicitly. However, the inherent smoothness constraint discourages discontinuity consideration. We propose a post-processing algorithm that integrates the input forward and backward fields, which are output by existing registration/matching algorithms, to produce more robust results. Given such a pair of input
more » ... lds, our algorithm alternately refines the fields by tensor belief propagation, and enforces inverse consistency in stochastic sense by generalized total least squares fitting. To show the efficacy of our stochastic inverse consistency approach, we first present results on very noisy fields. We then demonstrate improvement on existing stereo matching where occlusion is naturally handled by localizing violations of inverse consistency. Finally, we propose a novel application on image stitching, where stochastic inverse consistency is employed in structure deformation, in order to seamlessly align overlapping images with severe misalignment in structure and intensity.
doi:10.1109/cvpr.2008.4587400 dblp:conf/cvpr/YeungTSPVCS08 fatcat:xbi4gm5w25bj3etfggyf6xully