  A canonical Huffman sequence is characterized by a zero inner-product between
itself and each of its shifted copies, except at their largest relative shifts:
their aperiodic auto-correlation then becomes delta-like, a single central peak
surrounded by zeros, with one non-zero entry at each end. Prior work showed
that the few known families of Huffman sequences (of length $N = 4n-1$, for
integers $n > 1$, with continuously scalable elements) are based upon Fibonacci
polynomials. Related multi-dimensional ($nD$) Huffman arrays were designed, as
well as non-canonical quasi-Huffman arrays that also possess delta-like
auto-correlations. We examined links between these discrete sequences and
delta-correlated functions defined on the continuum, and provided simple
non-iterative approaches to successfully deconvolve $nD$ data blurred by
diffuse Huffman arrays. Here we describe new constructions for canonical
Huffman sequences. Examples of length $N = 4n+1$, $N = 2n$ and families of
arbitrary length are given, including scaled forms, as well as for
Fibonacci-based arrays with perfect periodic auto-correlations, that are zero
for all non-zero cyclic shifts. A generalization to include canonical sequences
with complex scale factors invokes an equally useful dual form of
delta-correlation. We also present $1D$ arrays with a much smaller dynamic
range than those where the elements are built using Fibonacci recursion. When
Huffman arrays (that are comprised of inherently signed values) are employed as
diffuse probe beams for image acquisition, a new two-mask de-correlating step
is described here that significantly reduces the total incident radiation dose
compared to a prior method that added a positive pedestal-offset.
