sk_wavelet — 2D `smoothing` op

• Data kinds: image → image

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

sk_wavelet: 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.*

*The output is shown in a viridis-like pseudo-colour (dark purple = low, yellow = high) so that a field of quantities — distance, phase, orientation, depth — can be read.*

*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).*

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

▸ sk_wavelet: other inputs (docs site)

*The 4th column is a colour (H,W,3) input. This op handles colour without crossing channels (it does not convolve the colour channel as a third spatial axis).*

Usage

Denoising via wavelet transform. Decomposes the image into the wavelet domain, discards small coefficients (regarded as noise) using BayesShrink-criterion thresholding, and then applies the inverse transform.

> The detailed description below is the original text — the summary and the headings are translated.

HALCON に直接対応するものは無い。実装は `restoration.denoise_wavelet(v) をそのまま [0,1]` に clip したもので、しきい値やウェーブレット基底はすべて skimage の既定値まかせ —— a, b は未使用(調整点が無い、最も枯れた設定でとりあえずノイズを落としたい時用)。

Detailed usage guide

• gallery2d_smoothing_rank family guide

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

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.

sk_wavelet 0.35 0.50

▸ Load this pipeline · Load & run

Runnable examples (verified samples that actually call this op)

• gallery2d_smoothing_rank — py -3.11 examples/gallery2d_smoothing_rank.py

• poc_prnu_camera_fingerprint — py -3.11 examples/poc_prnu_camera_fingerprint.py

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

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (`smoothing`)

gaussian · mean_box · bilateral · unsharp · sk_tv · sk_rolling_ball · sk_nlm · sk_tv_bregman

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

sk_wavelet — 2D smoothing op