  A technique is presented that automates the direction characterization of
curvilinear features in multidimensional solar imaging data sets. It is an
extension of the Rolling Hough Transform (RHT) technique presented by Clark,
Peek, and Putman (Astrophys. J. 789, 82, 2014), and it excels at rapid
quantification of spatial and spatiotemporal feature orientation even for low
signal to noise applications. It operates on a pixel-by-pixel basis within a
data set and reliably quantifies orientation even for locations not centered on
a feature ridge, which is used here to derive a quasi-continuous map of the
chromospheric fine structure projection angle. For time-series analysis, a
procedure is developed that uses a hierarchical application of the RHT to
automatically derive apparent motion of coronal rain observed off-limb.
Essential to the success of this technique is this paper's formulation for the
RHT error analysis as it provides a means to properly filter results.
