joint_histogram — IMGMETRICS information op

• Data kinds: image2d × image2d → image2d

• Call: import imgmetrics; imgmetrics.joint_histogram(a, b, bins=64, data_range=None) (or opsimgmetrics.get("joint_histogram"))

Usage

Joint histogram of two images (the normalised joint probability).

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

ビン幅は `data_range` から決める ―― 画像ごとに min/max で伸縮させると、

一様に暗い絵と一様に明るい絵の相互情報量が同じになるので。

Detailed usage guide

• image_difference_metrics 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)

• image_quality_metrics — py -3.11 examples/image_quality_metrics.py

Ops the type connects to (they accept image2d as input)

mse · rmse · psnr · ssim · ms_ssim · ssim_map · image_entropy · joint_entropy

Same category (information)

image_entropy · joint_entropy · mutual_information · normalized_mutual_information

*Provenance: imgmetrics.py — IMGMETRICS 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.