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Chapter 5 Optical Imaging and PSF/OTF/MTF


One-Sentence Goal
Under the linear shift-invariant (LSI) baseline, define and estimate PSF/OTF/MTF, build a system-level modulation transfer chain that accounts for pixel aperture, motion, and defocus, and constrain imaging sharpness and anisotropy with contractible metrics.


I. Scope & Targets

  1. Inputs
    • From Chapter 3 (mode binding): SRef.img = { I_lin, masks, mode_axes, tau_map, manifest.imaging.device }.
    • From Chapter 4 (radiometric harmonization): I_corr, L_eff (when energy conservation checks are required).
    • Optical/mechanical metadata: { pixel_pitch, a_px, b_px, f_eff, F_number, focus_pos, T_trans(λ), stab_trace }.
  2. Outputs
    • PSF(x,y), OTF(fx,fy), MTF(fx,fy), PTF(fx,fy); optionally field-dependent variants such as PSF(u; x,y).
    • Component factors: MTF_opt, MTF_defocus, MTF_motion, MTF_pixel, MTF_proc, and the system result MTF_sys.
    • Metrics & reports: MTF50, MTF10, anisotropy, alias_ratio, assert_report.optics, and manifest.imaging.optics.
  3. Boundaries
    This chapter assumes small-signal linear imaging and weak non-idealities; with strongly nonlinear ISP, report an “effective MTF” only.

II. Terms & Variables

  1. Coordinates & frequency domain
    • x,y (image plane in meters), fx,fy (cycles per meter), ρ = sqrt(fx^2 + fy^2).
    • Sampling & Nyquist: f_sx = 1 / pitch_x, f_sy = 1 / pitch_y, f_Nx = f_sx / 2, f_Ny = f_sy / 2.
  2. Core functions
    • PSF(x,y) (point spread function), ( ∫∫ PSF dx dy ) = 1.
    • OTF(fx,fy) = F{ PSF(x,y) }, MTF = | OTF |, PTF = arg( OTF ).
    • Pixel-aperture MTF: MTF_pixel(fx,fy) = sinc( π * a_px * fx ) * sinc( π * b_px * fy ).
    • Motion MTF (uniform linear motion, length d_m, motion direction forming angle θ with fx,fy):
      MTF_motion(fx,fy) = sinc( π * d_m * ( fx cosθ + fy sinθ ) ).
  3. Objective & aberrations
    • Pupil function P(u,v) = A(u,v) * exp( j * 2π * W(u,v) / λ ), with normalized pupil coordinates u,v.
    • W (wavefront aberration), λ (wavelength), F_number = f_eff / D_aperture.
  4. Quality & uncertainty
    u(x), coverage U = k * u_c, q_score, drift, SNR_edge.

III. Axioms P205- (Optics Baseline)*


IV. Minimal Equations S205-*


V. Imaging Transfer Estimation Process M50-*


VI. Contracts & Assertions


VII. Implementation Bindings I50-*


VIII. Cross-References


IX. Quality Metrics & Risk Control

  1. Key indicators
    MTF50, MTF10, anisotropy, alias_ratio, slope@0, u(MTF50), PTF_var, comp_residual.
  2. Risk handling
    • If MTF50 or alias_ratio violates limits: reduce publication resolution or enable anti-alias filtering; roll back to the last freeze_release optical parameters.
    • For field-dependent anomalies: mask hotspot regions or trigger refocus/mechanical re-alignment; down-rank q_score and record TraceID.

Summary
Centering on PSF/OTF/MTF, this chapter provides a unified path from data-driven estimation to system-level decomposition and composition—edge/point → PSF/OTF → MTF_components → MTF_sys—and enforces reproducibility and auditability across devices, fields, and environments through contract metrics and manifest signatures.


Copyright & License (CC BY 4.0)

Copyright: Unless otherwise noted, the copyright of “Energy Filament Theory” (text, charts, illustrations, symbols, and formulas) belongs to the author “Guanglin Tu”.
License: This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0). You may copy, redistribute, excerpt, adapt, and share for commercial or non‑commercial purposes with proper attribution.
Suggested attribution: Author: “Guanglin Tu”; Work: “Energy Filament Theory”; Source: energyfilament.org; License: CC BY 4.0.

First published: 2025-11-11|Current version:v5.1
License link:https://creativecommons.org/licenses/by/4.0/