AI 中文总结
本文将探测器相关的测量一致性引入叠层成像重建，构建空间分辨置信图嵌入迭代振幅约束，实现约两倍SNR增强，突破光电SNR限制，提升了叠层成像性能。
AI 中文摘要
叠层成像（Ptychography）是一种强大的无透镜成像技术，能够接近衍射极限，但其性能日益受到非理想探测硬件的制约。在光子受限测量中，微弱的高频衍射信号常与空间异质的探测器噪声重叠，而大多数重建算法仍将探测器视为理想测量平面。本文将探测器相关的测量一致性引入叠层成像重建，通过校准逐像素传感器响应，构建空间分辨置信图并将其嵌入迭代振幅约束，从而对不可靠的探测器残差进行降权，同时保留具有物理意义的衍射信息。在透射、反射及弱生物相位成像上的实验表明，该方法可提升衍射数据质量，实现约两倍的信噪比（SNR）增强，且重建结果达到瑞利极限，测得的k因子约为0.65。与现有先进去噪方法相比，所提框架在抑制探测器诱导背景与保留结构衍射信息间实现了更优平衡。这些结果表明，探测器可靠性可作为循环内物理约束，用于拓展存在不完美传感器的叠层成像性能。
英文摘要
Ptychography is a powerful lensless imaging technique capable of approaching the diffraction limit, yet its performance is increasingly constrained by non-ideal detection hardware. In photon-limited measurements, weak high-frequency diffraction signals often overlap with spatially heterogeneous detector noise, whereas most reconstruction algorithms still treat the detector as an ideal measurement plane. Here, we introduce detector-informed measurement consistency into ptychographic reconstruction. By calibrating the pixelwise sensor response, the method construct a spatially resolved confidence map and embed it into the iterative amplitude constraint, allowing unreliable detector residuals to be down-weighted while preserving physically meaningful diffraction information. Experiments across transmission, reflection, and weak biological phase imaging show improved diffraction-data quality, an approximately twofold signal-to-noise ratio (SNR) enhancement, and reconstruction approaching the Rayleigh limit with a measured (k)-factor of about 0.65. Compared with previous advanced denoising methods, the proposed framework achieves a better balance between suppressing detector-induced background and preserving structural diffraction information. These results show that detector reliability can be used as an in-loop physical constraint to extend the performance of ptychographic imaging with imperfect sensors.
Comments22 pages, 6 figures,
