Implement `TransformCollection` as an ITK external module

## Background

`itk_dreg.reduce_dfield` implements the `TransformCollection` class. `TransformCollection` extends the `itk.Transform` effective interface to composite results from multiple piecewise input transforms to a single point output. `itk_dreg.reduce_dfield` relies on `TransformCollection` to sample a single output deformation field result based on multiple subimage registration transforms.

## Current Implementation

`TransformCollection` is implemented as a pure Python class that runs sampling in serial. As a result, its execution time is rather slow.

Meanwhile as a pure Python class `TransformCollection` is not considered to be a subclass of `itk.Transform` and thus cannot be provided to ITK process objects as a valid input.

## Feature Request

We should create an ITK external module (`ITKTransformCollection`, `ITKTransformBlending`, `ITKPiecewiseTransform`, or similar) and re-implement `TransformCollection` there as an ITK C++ class.

Suggested steps:
1. Use [ITKModuleTemplate](https://github.com/InsightSoftwareConsortium/ITKModuleTemplate) to create the new external module project on GitHub
2. Implement a transform blending class virtual interface that accepts multiple output point candidates with attached piecewise transform domain information and yields a single point result. Consider whether it makes sense to inherit from or otherwise use or reference ITK interpolator classes.
3. Implement a simple averaging blending method in C++ that ports [`TransformCollection.blend_simple_mean`](https://github.com/InsightSoftwareConsortium/itk-dreg/blob/main/src/itk_dreg/reduce_dfield/transform_collection.py#L81) logic.
4. Implement an advanced distance-weighted blending method in C++ that ports [`TransformCollection.blend_distance_weighted_mean`](https://github.com/InsightSoftwareConsortium/itk-dreg/blob/main/src/itk_dreg/reduce_dfield/transform_collection.py#L105) logic.
5. Implement [`TransformEntry`](https://github.com/InsightSoftwareConsortium/itk-dreg/blob/main/src/itk_dreg/reduce_dfield/transform_collection.py#L17) in C++ according to the specification:
- Defines a transform with an optional bounds constraint. If an inclusive domain is specified, the transform is bounded and may only transform input points that fall within the domain. If no domain is specified the transform is unbounded and may transform any input point.
- Accepts an `itk.TransformBase` input
- Accepts an optional transform domain. I have used `Optional[itk.Image]` in `itk_dreg` to specify that a domain may be an oriented bounding box in 3D physical space as described by an unbuffered `itk.Image` with metadata. The equivalent representation in C++ would be `std::optional>`. There may be other valid specifiers for a generic 3D region that could be used.
- Maybe inherits from `itk.TransformBase` to define a `TransformPoint` function. This is not required, but would allow the `TransformEntry` to be used in generic ITK filters to describe a piecewise function. May be reasonable to effectively return a translation of 0 for any input points outside of a bounded domain.
- Consider using a more descriptive name, such as `PiecewiseTransformFunction`, `BoundedTransform`, etc.
7. Implement the C++ `TransformCollection` class according to the following specification:
- Derives from `itk.TransformBase`
- Accepts multiple `itk.TransformEntry` piecewise transform instances
- Accepts a blending function
- Implements `TransformPoint` such that:
1. Each piecewise transform entry in the collection is evaluated to determine whether the point falls within its bounds;
2. For each transforms whose bounds contains the input point, transform the point to return an output point candidate;
3. Apply blending to smooth among output point candidates to return a single output point.