Condition theory for image registration and post-registration error estimation


We present in this chapter applications of condition theory for image registration problems in a general framework that is easily adapted to a variety of image processing tasks. After summarizing the history and foundations of condition theory, a short analysis is given of computational sensitivity for point correspondence between images with respect to translation, rotation-scale-translation (RST), and affine pixel transforms. Several surprising results follow from this analysis, including the principal result that increasing transform complexity is mirrored by increasing computational sensitivity, i.e., KTrans ≤ KRST ≤ KAffine . The utility of condition-based corner detectors is also seen in the demonstrated equivalence between the translational condition number and the commonly used Shi-Tomasi corner function. These results are supplemented by a short discussion of sensitivity estimation for the computed transform parameters and any resulting registration misalignment.
C. Kenney, B. S. Manjunath, M. Zuliani and K. Solanki,
“Condition theory for image registration and post-registration error estimation”,
Image Registration for Remote Sensing’ edited by Jacqueline LeMoigne, Nathan Netanyahu and Roger Eastman, pp. 200-214, Cambridge University Press, 2011.
Node ID: 594 , DB ID: 404 , Lab: VRL , Target: Book
Subject: [Image Registration and Fusion] « Look up more