frequency op• Data kinds: image → image
• Call: fullseye.apply(img, "fft_image", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: fft_image (the HALCON reference is a useful guide to its meaning and parameters)
An image obtained by compressing the power spectrum of the 2D FFT with `log1p(|F|) and normalizing it. Already fftshift-ed so the low-frequency (DC) component sits at the center. Used to visualize the spatial frequency of periodic noise or texture. Corresponds to HALCON's fft_image` (Compute the fast Fourier transform of an image).
> The detailed description below is the original text — the summary and the headings are translated.
`a, b` は未使用 ―― 画像全体に対するグローバルな FFT で、窓関数や
帯域選択のような調整点は無い。
• gallery2d_texture_freq family guide
• 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.
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
frequency)lowpass · highpass · sk_butterworth · power_real · power_byte · phase_rad · highpass_image · bandpass_image
*Provenance: ops.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.