COMP: Use itk::Math::MatrixExponential instead of removed vnl_matrix_exp

[hjmjohnson]

VXL removed core/vnl/vnl_matrix_exp, which AffineLogTransform included via <vnl/vnl_matrix_exp.h> (InsightSoftwareConsortium/ITK#6452). This migrates the two call sites to itk::Math::MatrixExponential, an ITK-supported Eigen-backed replacement.

Depends on InsightSoftwareConsortium/ITK#6454 (adds itk::Math::MatrixExponential / itkMatrixExponential.h). Hold merge until an ITK containing it is required.

Change

-#include <vnl/vnl_matrix_exp.h>             →  #include "itkMatrixExponential.h"
-vnl_matrix_exp(... .GetVnlMatrix())         →  itk::Math::MatrixExponential(...)
-vnl_matrix_exp(A_bar)                        →  itk::Math::MatrixExponential(A_bar)

Call-site argument types (vnl_matrix_fixed, vnl_matrix) are unchanged; the new function provides matching overloads. Both AffineLogTransform and AffineLogStackTransform components rebuild clean against the new header.

[hjmjohnson]

Performance impact of migrating AffineLogTransform from vnl_matrix_exp to itk::Math::MatrixExponential. Freshly benchmarked on this transform's two call patterns (-O3 -DNDEBUG, best-of-11 min ns/call). Net: ~1.7–2× faster matrix-exp work per parameter-update, more accurate, results unchanged in practice.

Per-call timing + net AffineLogTransform impact

operation	vnl_matrix_exp	itk (Eigen)	Eigen vs vnl
log-domain 2×2 (SetParameters)	~99 ns	~410 ns	4.1× slower
log-domain 3×3 (SetParameters)	~150 ns	~510 ns	3.4× slower
A_bar 4×4 (Jacobian loop)	~1349 ns	~695 ns	1.95× faster
A_bar 6×6 (Jacobian loop)	~2681 ns	~1333 ns	2.0× faster

Per SetParameters (1 log-domain exp + d² augmented A_bar exps in PrecomputeJacobianOfSpatialJacobian):

	old (vnl)	new (Eigen)	net
2D	95 + 4·1331 = 5419 ns	405 + 4·692 = 3173 ns	~1.7× faster
3D	149 + 9·2676 = 24233 ns	503 + 9·1315 = 12338 ns	~2.0× faster

The d² A_bar Jacobian loop dominates and Eigen wins there, so net it's faster despite the single small log-domain exp being slower. Matrix-exp is a negligible slice of full registration wall-time, so end-to-end timing is effectively unchanged.

Numerical equivalence + accuracy

For near-identity log-domain matrices the absolute output difference between the two methods is ~1e-12 — far below any registration tolerance, so registration results are unchanged. Eigen (Higham scaling-and-squaring) is also ~2–3 orders of magnitude more accurate than vnl's Taylor series on the exp(A)·exp(−A)=I identity at every norm, and stays robust where the Taylor series degrades for large norms.

This PR depends on itk::Math::MatrixExponential landing in ITK (InsightSoftwareConsortium/ITK#6454).

[N-Dekker]

Thanks Hans. Would this compile for both ITK 5 and 6, when we add something like #if ITK >= 6 and put the original code in the #else?