Enhancing Ptychography Fidelity via Kurtosis Active Search for Robust Axial Optimization

Coherent diffraction imaging is a beamline microscopy technique based on diffraction that removes the resolution limit imposed by conventional imaging optics. However, the axial distance between the sample and the detector directly governs how the light filed propagates. Even minute errors in the distance can introduce phase distortion and misalignment, degrading image quality. Precisely measuring axial distance is often challenging due to the detector’s mechanical constraint. To overcome this limitation, we propose kurtosis active correction ptychography (KACP), a kurtosis-driven active search strategy for correcting axial distance errors in ptychographic reconstruction. The proposed method begins by computing an initial image from the diffraction pattern, followed by the Rayleigh–Sommerfeld diffraction formula to calculate multi-layer light field information. After each propagation step, the image’s kurtosis is calculated, and the axial distance that maximizes this kurtosis is selected as the optimal focus. This approach remains stable across a wide range of defocus states and axial offsets, greatly reducing the algorithm’s sensitivity to its initial distance estimate. Experimental validation demonstrates that KACP improves the reconstructed image resolution by a factor of two. Compared with conventional search methods based on image-sharpness metric or scanning-trajectory optimization, KACP achieves markedly higher reconstruction fidelity, enhanced robustness, and genuine global positioning accuracy. Moreover, its compatibility with a broad range of illumination sources and with both amplitude-type and phase-type specimens renders KACP a highly versatile platform for advanced diffraction imaging.