Constrained Linear Curvature Image Registration Model and Its Numerical Algorithm

Table 13

Dependent results of our new model on the regularizer parameter by testing Example 3 (Figures 5(a)–5(c)).

	0.1	0.2	0.3	0.4	0.5	0.6
(%)	0.0673	0.1104	0.1398	0.1634	0.1839	0.2025
	0.4410	0.4508	0.4566	0.4610	0.4647	0.4679

means that the transformation does not include folding or cracking.