tb_iqft2 — 2D `typed` op

• Data kinds: qimage → qimage

• Call: fullseye.apply(img, "tb_iqft2", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

tb_iqft2: input → output

*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*

*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*

Stages (the ops that come before → this op, left to right):

▸ tb_iqft2: stages (docs site)

On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):

▸ tb_iqft2: other inputs (docs site)

Usage

Inverse quaternion Fourier transform of a centred spectrum. → (H, W, 4).

The exact inverse of :func:qft2 for the same side and the same mu:

measured round-trip error `2.22e-15` for both sides on a standard-normal

`(32, 32, 4) field. The kernel is exp(+mu * 2*pi*(...))` applied on the

side named, and the `1/(H*W)` normalisation is carried here, as in

`numpy.fft.ifft2`.

Using the wrong side does not raise. `iqft2(qft2(q, "left"), "right")`

returns a finite, plausible quaternion image that is simply not `q`:

measured `max|err| = 1.113` on a random colour image whose own range is

`0.9994 (another seed: 1.063 against 1.0), and — the dangerous case — only 0.054` against a range of

`1.076` on a grey-axis-dominated one, which is small enough to survive a

look at the picture. The `side` argument is required at both ends for

exactly this reason, and the two calls must agree: nothing in the data

records which transform produced it, so nothing downstream can catch the

mismatch for you.

Raises `ValueError: *spectrum* is not a valid (H, W, 4)` field;

*side* is not `'left' / 'right'`; *mu* is not a finite non-zero

3-vector.

Typed bridge of the quat op `iqft2 into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

img_to_rgb 0.50 0.50
tb_rgb_to_quaternion 0.50 0.50
tb_iqft2 0.50 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

The examples below call the underlying ledger op iqft2. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).

• quaternion_monogenic — py -3.11 examples/quaternion_monogenic.py

Ops the type connects to (they accept `qimage` as input)

identity · tb_quaternion_to_rgb · tb_quat_norm · tb_quat_conjugate_image · tb_quat_normalize_image · tb_monogenic_amplitude · tb_monogenic_phase · tb_monogenic_orientation

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_iqft2 — 2D typed op