registration opimage2d × image2d → tableimport fullseye as fs; fs.ledger.phase_correlation_shift(image1, image2, window: 'str | None' = 'hann', whitening: 'float' = 0.5, method: 'str' = 'upsample', upsample_factor: 'int' = 100) -> 'dict' (実装を直接呼ぶなら import filters_freq; filters_freq.phase_correlation_shift(image1, image2, window: 'str | None' = 'hann', whitening: 'float' = 0.5, method: 'str' = 'upsample', upsample_factor: 'int' = 100) -> 'dict'、台帳から引くなら opsfit.get("phase_correlation_shift"))2 枚の画像の位置合わせに必要なサブピクセル移動量を位相限定相関で求める。
The default method="upsample" refines the whitening-aware periodic
FFT peak by evaluating a 1.5-pixel neighbourhood with a matrix-multiply
local DFT using only NumPy (upsample_factor=100 by default).
method="parabola" is faster, but its wrapped three-point parabola is
biased about 0.166 px toward the integer grid. On the fixed 96x112 truth
gates, parabola errors are 0.166 px (Hann) / 0.172 px (no window), versus
0.010 px for upsampling with either window; upsampling is required to stay
within 0.02 px and within 0.01 px of scikit-image when it is installed.
The local DFT follows Guizar-Sicairos, Thurman & Fienup (2008), Optics
Letters 33(2), 156-158, doi:10.1364/OL.33.000156. The sign convention is explicit: when
image2 = shift(image1, d), the result is approximately -d, so
shift(image2, result) approximately equals image1.
Returns row_shift/col_shift (also dy/dx), peak and
peak_ratio (largest peak divided by the best peak outside its 3x3
neighbourhood). Constant or relatively textureless inputs raise ValueError.
py -3.11 examples/fit_ops_from_knowhow.pytable を入力に取れる)—
registration)—
Provenance: filters_freq.py — FIT 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.