Phase retrieval with dynamic linear combination in multiple intensity measurements
Phase retrieval with dynamic linear combination in multiple intensity measurements
复制标题
DOI：
10.1016/j.optlaseng.2022.107200
复制
发表时间：
2022
影响因子：
4.6
通讯作者：
Xiu Wen;Yutong Li;Xuyang Zhou;Yu Ji;Keya Zhou;Shutian Liu;D. Chi;Dong Jia;Zhengjun Liu
中科院分区：
文献类型：
--
作者：
Xiu Wen;Yutong Li;Xuyang Zhou;Yu Ji;Keya Zhou;Shutian Liu;D. Chi;Dong Jia;Zhengjun Liu
在目前的多强度测量方法中，假设记录的不同强度图案具有相同的质量，并且不同图像对结果的贡献是相同的。然而，由于原始图像在数据采集过程中受到环境噪声和聚焦距离的影响，因此强度图像的质量是不同的。等权数据处理方案在多次强度测量中并不是最优的。为了提高相位恢复的分辨率和鲁棒性，提出了一种基于动态线性组合的相位恢复算法。在该算法中，每个模式被分配不同的权重，根据其质量在重建。应用图像质量评价函数来确定权重系数。通过对所有图像的线性组合重建出更高分辨率的图像，优于传统算法的上级性能。
In the present methods of multiple intensity measurements, the recorded different intensity patterns are supposed to have the identical quality and the contribution of different images to the result is the same. However, intensity patterns are of different quality, since the raw patterns are affected by environment noise and focusing distance in the process of data acquisition. The equal weight scheme in data processing is not optimum in the multiple intensity measurements. A novel, to the best of our knowledge, phase retrieval algorithm with dynamic linear combination is proposed to improve resolution and robustness. In the algorithm, each pattern is assigned different weight according to its quality during reconstruction. The image quality evaluation function is applied to determine the weight coefficient. A higher-resolution image is reconstructed by the linear combination of all images, which is superior to the conventional algorithm.