scale_clip — 2D `gray` op

• Data kinds: image → image

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

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

Usage

Linear tone transformation via gain and offset. Equivalent to HALCON's `scale_image` (Scale the gray values of an image.).

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

`a がゲイン（コントラスト）を 0.5〜2.0 倍に、b がオフセット（明るさ）を -0.5〜+0.5 に振る（clip(gain*v + offset, 0, 1)）。b=0.5` がオフセット 0（変化なし）に対応する点に注意。

Detailed usage guide

• gallery2d_gray_arith 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_gray_arith — py -3.11 examples/gallery2d_gray_arith.py

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

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

Same category (`gray`)

gamma · invert · equalize · sigmoid · clahe · sk_adapthist · sk_enhance_contrast · sk_autolevel

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

scale_clip — 2D gray op