depth op• Datenarten: lightfield → image2d
• Aufruf: import lightfield; lightfield.lf_depth_from_focus(lf, slopes=(-2.0, -1.0, 0.0, 1.0, 2.0), *, window=9, measure='laplacian', subpixel=True, interp='linear', edge='nearest') (oder opslightfield.get("lf_depth_from_focus"))
Steigung pro Pixel aus dem Schärfemaximum über den Refokussierdurchlauf.
> Die ausführliche Beschreibung unten ist der Originaltext — Zusammenfassung und Überschriften sind übersetzt.
Refocus at every slope in *slopes*, measure local sharpness (*measure*:
`laplacian` = summed modified Laplacian, the classical depth-from-focus
operator; `variance = local variance; gradient` = local gradient
energy) in a `window x window` neighbourhood, and take the slope at which
each pixel is sharpest. With `subpixel=True` (default) the peak is refined
by fitting a parabola through the winning sample and its two neighbours on a
uniformly spaced sweep — on a non-uniform sweep the refinement is
skipped rather than applied with the wrong spacing.
Unbiased where :func:lf_epi_slope is not: measured 2026-09-01 on a
5x5x64x64 synthetic field over a 121-point sweep from -3 to +3, the argmax
landed exactly on the true slope in 18 of 18 combinations (true slopes
0.0, +0.5, +1.0, +1.5, +2.0, -1.0 crossed with texture sigma 1.5 / 3.0 /
5.0 px), and the sub-pixel refinement left every one of them unmoved. Its
resolution, though, is whatever you put in *slopes* — it cannot see a plane
you never refocused on.
Returns `(slope_map, sharpness): the (H, W)` map of estimated slopes
(in px per angular step) and the `(H, W)` peak focus-measure value, which
is the honest confidence — a textureless pixel has no sharpness peak, gets
an essentially arbitrary slope, and its `sharpness` is ~0. Threshold on it
rather than trusting the map everywhere.
Raises `ValueError`: *lf* not a valid light field, *slopes* empty /
over :data:MAX_STACK_SLICES / over :data:MAX_STACK_ELEMENTS / containing
a non-finite or over-large value, an even or non-positive *window*, unknown
*measure* / *interp* / *edge*.
• Leitfaden zur Familie lightfield_depth
• Katalog der Beispieldaten (Download-URLs / Lizenzen) — 2-D nutzt skimage.data (BSD/Public Domain) plus synthetische Bilder, 3-D nennt Download-URLs echter Datenquellen (Stanford, PDS, …).
• Herkunft und Literatur der Operatoren — die Quellen der Forschung/Verfahren, auf denen diese Operatorfamilie beruht.
• Der kanonische Algorithmus (Autor, Jahr) und seine Anwendungen stehen im Familienleitfaden oben.
• lightfield_depth — py -3.11 examples/lightfield_depth.py
• poc_lightfield_depth — py -3.11 examples/poc_lightfield_depth.py
image2d als Eingabe)lf_from_mla · lf_disparity_to_depth · lf_all_in_focus
depth)lf_epi_slope · lf_disparity_to_depth · lf_all_in_focus · lf_plenoptic_design
*Provenance: lightfield.py — LIGHTFIELD Operator-Registry. Diese Notiz wird von tools/opdocs.py md erzeugt (nicht von Hand bearbeiten).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.