一种基于共轭梯度的正则化OT图像重建算法  

A Regularized Reconstruction Method for Optical Tomography Based on Conjugate-gradient

作　　者：金永明[1] 王加俊[1] 

机构地区：[1]苏州大学电子信息学院,江苏苏州215021

出　　处：《微电子学与计算机》2006年第7期96-98,101,共4页Microelectronics & Computer

基　　金：国家自然科学基金项目(30300088)

摘　　要：文章基于OT扩散方程模型提出了一种正则化共轭梯度OT图像重建算法,通过引入图像熵和局部平滑函数为正则化项以克服重建问题中的病态特性。与简单的共轭梯度重建算法相比,重建图像的MSE值分别为0.4413*10-4和0.4819*10-4。研究表明,正则化的OT图像重建算法能有效降低重建中的病态性,提高图像重建质量。A new regularized conjugate-gradient reconstruction algorithm for optical tomograpy based on diffusion equation is presented in this article. In order to improve the ill-poseness in reconstruction process, two criterions with smoothness -the image entropy and the local smoothing function are incorporated as the regularized items. Compared with the reconstruction without regularized items, the MSE of the image are 0.4413×10^-4 and 0.4819×10^-4. The results show that this regularized reconstruction algorithm can effectively decrease the ill-posedness of the reconstruction and improve reconstruction quality.

关 键 词：(OT)光学层析成像 扩散方程 正则化 最大熵 局部平滑函数 共轭梯度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]