polarization_render — SPECULAR `polarization` op

• 資料種類:image2d × image2d → polsweep

• 呼叫:import specularity; specularity.polarization_render(diffuse, specular, angles_deg=(0.0, 45.0, 90.0, 135.0), azimuth_deg=0.0)(或 opsspecular.get("polarization_render"))

用法

偏振片旋轉的正向模型:把已知的分離變成偏振相機會記錄到的影格序列。→ (N, H, W)。

> 以下的詳細說明為原文 —— 摘要與標題已翻譯。

`I(t) = 0.5 * diffuse + specular * cos^2(t - azimuth)`. The diffuse term is

treated as completely unpolarised, so it contributes half its radiance at

every analyser angle; the specular term is treated as completely linearly

polarised at *azimuth_deg*, so it follows Malus's law. Those are the two

assumptions :func:polarization_separate inverts, and rendering with them

is how the inversion gets a ground truth to be exact against.

Physically the assumptions hold near Brewster's angle for a dielectric and

fail at normal incidence; the module docstring says where. This operator

does not model the incidence angle at all — it takes the two radiance maps

you specify and produces the sweep they imply.

Raises `ValueError`: *diffuse* / *specular* are not 2-D arrays of the

same shape, or are complex / masked / non-finite / string-typed; either has

a negative value (a negative radiance is not a scene); *angles_deg* has

fewer than 3 entries or does not determine the three unknowns.

詳細使用指南

• specular_photometric 族使用指南

參考(範例資料・文獻)

• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。

• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。

• 演算法的正典(作者・年份)與用途見上面的族使用指南。

可執行的範例(實際呼叫該運算子並已驗證的樣例)

• specular_photometric — py -3.11 examples/specular_photometric.py

型別可銜接的下一個運算子(可接受 `polsweep` 作為輸入)

polarization_separate · polarization_dolp_map · polarization_stokes

同類別(`polarization`)

polarization_separate · polarization_dolp_map · polarization_stokes

*Provenance: specularity.py — SPECULAR 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*

polarization_render — SPECULAR polarization op

用法