A Diffraction Imaging Algorithm Based on Gaussian Mixture Model

LIAN Qiu-sheng; HOU Ya-wei; SU Yue-ming; SHI Bao-shun

doi:10.3969/j.issn.0372-2112.2018.10.006

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A Diffraction Imaging Algorithm Based on Gaussian Mixture Model

更新时间：2025-07-16

- A Diffraction Imaging Algorithm Based on Gaussian Mixture Model
- Acta Electronica Sinica Vol. 46, Issue 10, Pages: 2347-2350(2018)
- 作者机构：
  
  燕山大学信息科学与工程学院,河北,秦皇岛,066004
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61471313);Natural Science Foundation of Hebei Province (No.F2014203076)
- DOI：10.3969/j.issn.0372-2112.2018.10.006
  CLC： TN911.73
- Published Online：25 October 2018，
  
  Published：2018
- 稿件说明：
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LIAN Qiu-sheng, HOU Ya-wei, SU Yue-ming, et al. A Diffraction Imaging Algorithm Based on Gaussian Mixture Model[J]. Acta Electronica Sinica, 2018, 46(10): 2347-2350.
DOI：

LIAN Qiu-sheng, HOU Ya-wei, SU Yue-ming, et al. A Diffraction Imaging Algorithm Based on Gaussian Mixture Model[J]. Acta Electronica Sinica, 2018, 46(10): 2347-2350. DOI： 10.3969/j.issn.0372-2112.2018.10.006.

摘要

编码衍射成像系统中记录的测量值丢失了相位，而相位含有关于图像的大部分结构信息.如何利用无相位测量值重构原始图像是相位恢复（Phase Retrieval，PR）算法面临的一个重要问题.由期望最大（EM）算法训练高斯混合模型（GMM）的最优参数，任一图像块可以选用GMM中某一模型分量最佳表示.基于该认识，本文利用GMM的统计特性融合数据保真项构造PR优化问题，并用加速邻近梯度法求解该问题.实验结果表明，该算法在噪声强度较大、编码衍射图案较少的情况下仍能获得较高质量的图像重构.

Abstract

The phase information of the recorded measurements is lost in the coded diffraction imaging system. However

the phase contains most of structural information about the image. How to reconstruct the original image from measurements without phase information is a crucial problem faced by the phase retrieval algorithms. The optimal parameters of the Gaussian mixture model (GMM) are trained by the expectation maximization (EM) algorithm. An image patch can be represented optimally by one of the components in the GMM model. Based on this fact

a PR optimization problem which fuses the statistical properties of GMM and the data fidelity term is formulated. Moreover

the accelerated proximal gradient method is utilized to solve this problem. The experimental results show that the proposed method can achieve high-quality image at the case of few coded diffraction patterns and high noise levels.

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