极大似然噪声估计的高动态范围叠层衍射成像术
High-Dynamic-Range Ptychography Using Maximum Likelihood Noise Estimation
李文杰 1谷洪刚 2刘力 1钟磊 1周玉 1刘世元2
作者信息
- 1. 华中科技大学智能制造装备与技术全国重点实验室,湖北 武汉 430074
- 2. 华中科技大学智能制造装备与技术全国重点实验室,湖北 武汉 430074;光谷实验室,湖北 武汉 430074
- 折叠
摘要
衍射场作为叠层衍射成像技术(ptychography)的重要约束,其信息的丰富度和准确性将直接影响重构质量.提出一种基于极大似然噪声估计的高动态范围(ML-HDR)叠层衍射成像方法,即在探测器线性响应假设下,构建复合高斯噪声模型,根据极大似然估计求解最优权重函数,由多张低动态范围衍射场合成高信噪比衍射场.对比了单次曝光、传统HDR和ML-HDR三种方法的重构质量.仿真和实验结果表明:相比单次曝光,ML-HDR能将动态范围拓宽8位,重构分辨率提升至2.83倍;相比传统HDR,ML-HDR能提高重构图像的均匀性和对比度,且无需额外标定硬件参数.
Abstract
As crucial constraints of ptychography,the richness and accuracy of diffraction patterns directly affect the quality of reconstruction images.This paper proposes a high-dynamic-range ptychography using maximum likelihood noise estimation(ML-HDR).Herein,assuming the linear response of the detector,a compound Gaussian noise model is established;the weight function is optimized according to the ML estimation;and a high signal-to-noise ratio diffraction pattern is further synthesized from multiple low dynamic range diffraction patterns.The reconstruction quality of single exposure,conventional HDR,and ML-HDR is compared.The simulation and experiment results show that ML-HDR can widen the dynamic range by 8 bits and enhance the reconstruction resolution by 2.83 times compared with the single exposure.Moreover,compared with conventional HDR,ML-HDR can enhance the contrast and uniformity of the reconstruction image in the absence of additional hardware parameters.
关键词
计算成像/叠层衍射成像术/高动态范围/相位恢复/极大似然估计Key words
computational imaging/ptychography/high dynamic range/phase retrieval/maximum likelihood estimation引用本文复制引用
基金项目
国家自然科学基金(52130504)
湖北省重点研发计划(2021BAA013)
出版年
2024
NETL
NSTL
万方数据