simulate_defocus — 2D `smoothing` op

• Data kinds: image → image

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

• HALCON equivalent: simulate_defocus (the HALCON reference is a useful guide to its meaning and parameters)

Usage

Smoothing that simulates uniform out-of-focus blur (defocus). Implemented as a rectangular-window mean filter (box filter, `ndimage.uniform_filter), approximating with a square window rather than the true blur shape from a circular aperture (circle-of-confusion). a sets the window width to one of four levels, 3/5/7/9 (_k(a)`), and b is unused.

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

HALCON の `simulate_defocus`（一様なピンボケをシミュレートする演算）に相当するが、光学的に正しい円形ボケではなく矩形平均という粗い近似である点に注意。

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.

Runnable examples (verified samples that actually call this op)

• gallery2d_smoothing_rank — py -3.11 examples/gallery2d_smoothing_rank.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_wavelet · sk_rolling_ball · sk_nlm

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

simulate_defocus — 2D smoothing op