convol_image — 2D nary op

• Data kinds: image × image → image

• Call: this op takes 2 inputs, so fullseye.apply cannot run it (that is the one-image model). g = fullseye.FullseyeGraph(); g.add("out", "convol_image", ["$in1", "$in2"], a=0.5, b=0.5); g.run({"$in1": img1, "$in2": img2}, terminal="out") (names starting with $ are the inputs you pass in)

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

Usage

> This operator's description has not been translated yet. The original text follows as it is.

第 2 入力をフィルタマスクとして畳み込む。HALCON の `convol_image に相当。★HALCON と同じく**相関**(マスクを書いたまま重ねる)で計算する —— scipy の convolve はマスクを反転するので、非対称なマスクだと画像が逆向きにずれる。マスクは絶対値の総和で正規化し、端は reflect。a, b` は未使用。

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.

Runnable examples (verified samples that actually call this op)

• (none yet)

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

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

Same category (nary)

add_image · sub_image · mult_image · div_image · abs_diff_image · max_image · min_image · bit_and

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

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.