基于极大似然模型和期望最大化算法的闪光图像重建

针对闪光照相图像低信噪比的特点，研究了带约束的基于极大似然模型和期望最大化算法（ML-EM）的闪光照相图像重建算法。该算法在ML-EM迭代重建算法的基础上，根据闪光照相图像低信噪比的特点及被重建客体具有分段平滑的先验信息，在迭代重建的过程中进行了相应的噪声抑制，抑制了噪声对重建结果的影响，同时很好地保持了客体的边界特征。数值模拟结果表明，基于噪声约束的ML-EM重建算法能取得较好的重建效果。

Image reconstruction algorithm based on maximum likelihood-expectation maximum for radiography

To improve the reconstruction quality of flash X-ray radiography containing noises, an image reconstruction algorithm based on ML-EM (maximum likelihood-expectation maximum) for radiography is studied. According to the characters of low signal to noise ratio and smoothness in pieces, proper filter restraining the noises during the processing of reconstruction is adopted, the result reconstructed by this algorithm is less influenced by noises and preserves the boundary character of the object. Simulation indicates that ML-EM reconstruction algorithm based on noises constraint can give satisfactory results.