jpeg_ghost_quality — IMGFORENSICS compression op

• Data kinds: images → image2d

• Call: import imgforensics; imgforensics.jpeg_ghost_quality(ghosts, qualities=None) -> 'np.ndarray' (or opsimgforensics.get("jpeg_ghost_quality"))

Usage

A series of ghost maps → a map of the quality at which each pixel's residual is smallest. `image2d`.

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

`qualities を省くと :func:jpeg_ghost_map` の既定(40..95 step 5)を仮定する

—— **枚数が合わなければ :class:ValueError**(添字と品質がずれた地図を返さない)。

返りは品質そのものを画素値に持つ `(H, W)` なので、値域は [0, 1] ではない。

表示するときは正規化すること(この op は数値を返すのであって絵を返さない)。

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_forensics_audit — py -3.11 examples/image_forensics_audit.py

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

perceptual_hash · fingerprint_correlate · error_level_map · jpeg_quality_estimate · jpeg_ghost_map · noise_inconsistency_map · copy_move_regions · watermark_embed

Same category (compression)

error_level_map · jpeg_quality_estimate · jpeg_ghost_map

*Provenance: imgforensics.py — IMGFORENSICS 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.