dc_homomorphic — 2D decomposition op

• Data kinds: image → image

• Call: fullseye.apply(img, "dc_homomorphic", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Homomorphic filter: high-emphasis of log(I) in the Fourier domain -> [0,1].

Attenuates low frequencies (illumination) and boosts high frequencies

(reflectance detail). a sets the cutoff radius; b the high/low gain spread.

Detailed usage guide

• gallery2d_texture_freq family guide

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)

• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py

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

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (decomposition)

dc_structure_texture · dc_texture_residual · dc_rpca_lowrank · dc_rpca_sparse · dc_retinex · dc_local_contrast_norm

*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.