add_noise_white — 2D `noise` op

• Data kinds: image → image

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

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

add_noise_white: 入力 → 出力

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*

Usage

Adds Gaussian white noise (generated with `np.random.default_rng, standard deviation 0.02+0.2*b). The random seed is deterministically derived from a via int(a*997)+7, so the same a always reproduces the same noise pattern (note that this is not truly random — a is used as a pseudo-knob that selects a "noise appearance type"). Corresponds to HALCON's add_noise_white` (Add noise to an image.).

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

`a は乱数シード(=ノイズパターン)を、b` はノイズの強さ(標準偏差)

を振る。両方が使われるが、`a` の意味は「強さ」ではなく「パターン」で

ある点が他の op と異なる。

Detailed usage guide

• gallery2d_smoothing_rank family guide

Background guides (the physics and conventions behind this op)

• mv_image_sensors — 産業用イメージセンサ（現行品中心）

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.

add_noise_white 0.50 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

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

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

Same category (`noise`)

add_noise_distribution

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

add_noise_white — 2D noise op