decompose op• データ種: image2d → table
• 呼び出し: import fullseye as fs; fs.ledger.complex_steerable_decompose(image, scales: 'int' = 4, orientations: 'int' = 4) -> 'dict' (実装を直接呼ぶなら import motionmag; motionmag.complex_steerable_decompose(image, scales: 'int' = 4, orientations: 'int' = 4) -> 'dict'、台帳から引くなら opsmotionmag.get("complex_steerable_decompose"))
1 フレームの複素・方位選択的サブバンド分解 → dict。
> 以下の詳細説明は原文のままです —— 要約と見出しは訳出済み。
Splits the image into scales * orientations analytic sub-bands plus three residuals (low-pass, high-pass and a small symmetric completion band). Each sub-band is a full-resolution (H, W) complex array whose modulus is the local contrast of that scale/orientation and whose argument is the local phase — the quantity a translation shifts linearly, which is what the rest of this module is built on. There is no spatial decimation: keeping every band at full resolution costs memory but makes the frame exactly invertible, and exactness is the point.
Returns {"bands": [complex (H, W), ...], "kinds": [...], "centre_cycles_per_px": [...], "orientation_rad": [...], "shape": (H, W), "scales": s, "orientations": k}. kinds[j] is "band" for an oriented sub-band and "lowpass" / "highpass" / "residual" otherwise; centre_cycles_per_px and orientation_rad are None for residuals, which have no orientation and no single centre frequency.
Feed the whole dict back to complex_steerable_reconstruct. Round trip error, measured on a 64x64 random frame with the defaults, is max|out - in| = 6.66e-16; on a 31x37 (odd, non-square) frame 7.22e-16; and the worst over every scales in 1..8 crossed with every orientations in 1..16 on 32x32 is 7.77e-16 — the tight-frame construction is exact, not approximate (see the notes on the self-conjugate grid points
in _filter_bank).
References: Freeman & Adelson, IEEE PAMI 1991; Simoncelli & Freeman, ICIP 1995; Portilla & Simoncelli, IJCV 2000.
• motion_magnification ファミリ ガイド
• サンプルデータ カタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
• 演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
• アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。
• motion_magnification — py -3.11 examples/motion_magnification.py
table を入力に取れる)decompose)*Provenance: motionmag.py — MOTIONMAG operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.