imaging_sim op• 数据种类:image2d × table → image2d
• 调用: import fullseye as fs; fs.ledger.render_through_lens(image, system, pixel_pitch_um=5.5, field_of_view=None, zones=3, noise=None, seed=0, illumination='traced', size=None, oversample=None)(要直接调用实现,import lensimage; lensimage.render_through_lens(image, system, pixel_pitch_um=5.5, field_of_view=None, zones=3, noise=None, seed=0, illumination='traced', size=None, oversample=None);从台账取用则 opsoptics.get("render_through_lens"))
把理想辐照度图像渲染成 *system* 背后的传感器会记录到的样子(image2d)。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
*image* (H×W, non-negative) is the ideal (paraxial) image on a sensor of *pixel_pitch_um* pixels centred on the optical axis; with *field_of_view* (half field to the sensor corner: degrees for an object at infinity, object height in mm otherwise) the picture is first zoomed so the corner sees that field. Pipeline: (a) inverse distortion remap (distortion_map grid, scipy.ndimage.map_coordinates order 1); (b) spatially varying blur — a zones×zones lattice of tile centres, each with its own pixel-integrated psf_from_opd (the +y-field PSF rotated to the tile azimuth), blended with bilinear (tent) weights so seams vanish; (c) relative illumination: "traced" = fraction of the field's ray bundle that reaches the image (vignetting, from raytrace.ray_bundle) normalised to the axis, times cos⁴ (obliquity, objects at infinity only), "cos4" = the classic law alone, "none"; (d) sensor, when *noise* is True or a dict {"full_well": 20000, "read_e": 3.0, "bits": 12, "exposure": 1.0, "dark_e": 0.0}: electrons = irradiance × exposure × full_well, Poisson shot noise (photoncount.photon_sample), Gaussian read noise, quantisation to *bits*, returned as DN/(2^bits − 1). With noise=None the float irradiance is returned untouched (deterministic; the noisy path is deterministic for a given *seed* too).
*oversample* defaults to whatever keeps at least 2 PSF samples per pixel (max(4, ceil(2·λ·F#/pitch))). Ground truth: a δ image through the f/2 paraboloid gives the pixel-integrated Airy PSF; a checkerboard through it comes back undistorted (correlation > 0.99); energy is conserved to 1 % with illumination off; noise off is bit-reproducible.
optics 的每个算子都先校验输入再计算(不让任何东西无声通过):
• 单位写进参数名 —— _mm / _um / _deg / _mrad。把 mm 和 µm 弄混不会崩溃,而是给出「看着合理却是错的答案」,所以用命名来防。这里绝不从数值大小去猜单位。
• 字符串一律 ValueError —— float('50') 会成功,于是未解析的配置值会被当成长度混进来(实测:thin_lens('50', '200') 曾返回看着合理的 66.667 mm)。bool 也按 True == 1 的隐式提升拒绝。
• complex / masked array 一律 ValueError(仅接受实数槽位;拒绝无声丢弃虚部或剥掉掩码)。所有输入中的 NaN/Inf 一律 ValueError。
• 逐项点名拒绝除零及其近亲:焦距 0、曲率半径 0、折射率 <= 0、全不透明光阑(全为 0,归一化变成 0/0)、总和 <= 0 的 PSF、S0 = 0 的 Stokes 矢量、物体位于前焦点(像在无穷远)。
• 只有两个算子会返回非有限值,而且都写进了契约:depth_of_field 在超焦距以外返回 far_mm = inf(这正是超焦距的定义),gaussian_beam 在束腰处返回 wavefront_radius_mm = inf(平面波前的曲率半径)。两者都同时返回一个有限的搭档(far_is_infinite / curvature_per_mm)。除此之外的无声 NaN/Inf 都在内部检出并 ValueError ——「float64 溢出了」和「答案是无穷大」是两种不同的主张,不能拿后者的脸去交付前者。
• 尺寸上限:生成网格受 optics.MAX_GRID(4096)限制,传入的场/PSF/光阑受 optics.MAX_FIELD_ELEMENTS(2^24),ABCD 元件序列受 optics.MAX_SYSTEM_ELEMENTS(1024),Zernike 受 MAX_ZERNIKE_TERMS(512)/ MAX_ZERNIKE_ORDER(40)/ MAX_ZERNIKE_BASIS(2^25)。以 fail-closed 堵住「小参数引发巨大内部分配」的路径(实测:n_max=40 × 4096² 需要 108 GB)。
• 物理上不可能的状态同样拒绝:偏振度 > 1 的 Stokes 矢量、负透过率、负强度、n-|m| 为奇数等非法 Zernike 指标。
• mv_cables — 线缆(规格、速度、供电、机器人线缆)
• mv_cameras — 工业相机厂商(与传感器的对应、线扫描 / TDI)
• mv_frame_grabbers — 图像采集卡(不属于光学系统,却决定能否采到图像)
• mv_image_sensors — 工业图像传感器(以现行产品为主)
• mv_standards — 相机接口规格与标准组织
• virtual_machine_vision — 虚拟机器视觉 —— 梳理参数与对象模型
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
• 算法的正典(作者、年份)与用途见上面的族使用指南。
• lens_defect_dataset_demo — py -3.11 examples/lens_defect_dataset_demo.py
image2d 作为输入)fraunhofer_pattern · pupil_psf · pupil_blur · psf_to_mtf · edge_spread · veiling_glare_index · emva_pair_statistics · emva_defect_pixels
imaging_sim)psf_from_opd · distortion_map · defect_dataset · calibration_views
*Provenance: lensimage.py — OPTICS 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.