Figure presents the PP data for one crossline of the data set in study. Observe the holes in the data due to irregularities in the geometry acquisition.
Biondi and Vlad examined the differences among regularizing the data with normalization, regularization with the leaky integration operator and regularization with the AMO operator. They conclude that the precondition of the regularized least-squares problem with the AMO operator yields more continuous results.
On this part of the problem, we only present the final interpolation results using normalization and AMO regularization. Figure presents the fold maps calculated using both normalization (top) and AMO regularization (bottom). Note that even though the fold maps are similar, as expected, the fold distribution is smoother using AMO regularization. Also note that with AMO regularization, the fold reduces to the half. This fact affects the final solution of the least-squares problem.
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Figure 3 Fold, using normalization (top) and AMO regularization (bottom) |
Figure compares the result of geometry regularization using normalization (top) and AMO regularization (bottom). Differences lie in the amplitudes and the borders.