frequency op• Data kinds: image → image
• Call: fullseye.apply(img, "xwt_mra_component", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
One level's detail component from multiresolution analysis (MRA, `pywt.mra2). Performing a 3-level MRA decomposition with db2` yields horizontal/vertical/diagonal components at each level as images at the same resolution as the original image (unlike ordinary wavelet decomposition, they are not downsampled). Here, one level is selected and a composite detail image -- horizontal + vertical + diagonal summed -- is min-max normalized and returned.
> The detailed description below is the original text — the summary and the headings are translated.
`a はどの段を見るか(1〜3 段目、min(3,1+int(a*3))。近似成分[0 段目]は選ばれない)を振る。b` は未使用。段が大きいほど粗いスケールのディテールになる。
• 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 · fft_image · power_real · power_byte · phase_rad · highpass_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.