typed op• 데이터 종류: lightfield → image
• 호출: fullseye.apply(img, "tb_lf_epi_slope", a=0.5, b=0.5)(2-D 는 이미지 1 장 + 스칼라 노브 2 개 a,b∈[0,1] 모델)
*그림 없음: 이 연산자는 lightfield를 입력으로 받습니다. 이미지에서 시작하는 Studio 프로그램으로는 그 타입에 닿지 않으므로 아래의 실행 가능한 예제를 보세요.*
EPI 직선 방향으로부터 구한 픽셀별 기울기(구조 텐서, 1회 처리).
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
A scene point traces a straight line in the epipolar-plane image
(:func:lf_epi), so along that line the intensity is constant:
`E_u + s * E_x = 0`. Accumulating that constraint over the whole angular
grid and a `window x window` spatial neighbourhood gives the closed-form
least-squares slope `s = -(J_ux + J_vy) / (J_xx + J_yy)` with
`J_ab = sum(E_a * E_b)` — one pass over the light field, no sweep, both
the horizontal and vertical EPI directions pooled.
This estimator is biased, and the bias is the reason to also run
:func:lf_depth_from_focus. It is ordinary (not total) least squares on
finite differences, so it needs the EPI line to advance less than roughly
one texture correlation length per view. Measured 2026-09-01 on
5x5x64x64 synthetic fields, median over the interior: with texture
`sigma = 1.5 px, true +1.00 -> +1.0004, +0.50 -> +0.5285`,
`+1.50 -> +1.3018, +2.00 -> +1.4614; with sigma = 5.0` px the same
slopes give `+1.0003, +0.5029, +1.4827, +1.9482`. Integer
slopes on a wrapped field come back within 4e-4 and `s = 0` is exact;
`|s| > 1 is under-estimated, by 27% at s = 2` on the roughest texture.
Use it as a fast dense initialiser, not as the final word.
Returns `(slope_map, energy): the (H, W) slope map and the (H, W)`
gradient energy `J_xx + J_yy` that was the denominator. Pixels whose
energy is below *min_energy* have no measurable parallax (a flat patch
of sky); their slope is set to 0 and their energy reported as-is, so you
threshold on `energy` instead of being handed a plausible-looking number
divided by ~0.
Raises `ValueError`: *lf* not a valid light field, an angular/spatial
shape where *neither* EPI direction carries information (the horizontal EPI
needs `U >= 2 **and** W >= 2, the vertical needs V >= 2` and
`H >= 2`), an even or non-positive *window*, a non-positive *min_energy*.
Typed bridge of the lightfield op `lf_epi_slope into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. This op has no tunable parameter; a and b` are unused.
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• (아직 없음)
image 를 입력으로 받는 것)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal
*Provenance: ops.py — 2D 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.