揭示计算成像的11种基本构件与3大故障根源，构建通用设计语言。
Eleven Primitives and Three Gates: The Universal Structure of Computational Imaging
- 所有成像模型可分解为11种物理基元构成的有向无环图。
- 重建失败仅由信息不足、载体噪声、算子错配三类原因导致。
- 适用于五类载体的12种成像系统，部署后图像质量提升0.8至13.9 dB。
计算成像系统——从编码孔径相机到冷冻电镜——横跨五类载体却具有隐藏的结构简洁性。我们证明，每个成像前向模型均可分解为恰好11种物理类型基元构成的有向无环图（有限基元定理），构成设计任意成像模态的组合语言。进一步证明，所有重建失败仅有三个独立根因：信息不足、载体噪声、算子错配（三元分解）。三个门控对应系统生命周期：门1和门2指导设计（采样几何、载体选择）；门3负责部署阶段校准与漂移修正。在12种模态及全部五类载体上验证了上述结论，部署仪器图像恢复增益达+0.8至+13.9 dB。11个基元与3个门共同建立首个计算成像系统的设计、诊断与纠错通用语法。
原文摘要 · Abstract (English)
Computational imaging systems -- from coded-aperture cameras to cryo-electron microscopes -- span five carrier families yet share a hidden structural simplicity. We prove that every imaging forward model decomposes into a directed acyclic graph over exactly 11 physically typed primitives (Finite Primitive Basis Theorem) -- a sufficient and minimal basis that provides a compositional language for designing any imaging modality. We further prove that every reconstruction failure has exactly three independent root causes: information deficiency, carrier noise, and operator mismatch (Triad Decomposition). The three gates map to the system lifecycle: Gates 1 and 2 guide design (sampling geometry, carrier selection); Gate 3 governs deployment-stage calibration and drift correction. Validation across 12 modalities and all five carrier families confirms both results, with +0.8 to +13.9 dB recovery on deployed instruments. Together, the 11 primitives and 3 gates establish the first universal grammar for designing, diagnosing, and correcting computational imaging systems.
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