基于不完全投影数据的气体扩散分布重建迭代层析成像算法的研究

发布时间：2018-03-15 00:27

本文选题：迭代重建　切入点：层析成像　出处：《合肥工业大学》2015年硕士论文　论文类型：学位论文

【摘要】：迭代层析成像算法在不完全投影数据的重建问题中应用广泛。光学遥感结合层析成像重建区域污染气体分布是典型的少投影方向的不完全投影数据重建问题,由于光学仪器贵重,出于成本上的考虑,无法布置很多组射线束以形成复杂的交叉光路；同时气体扩散大多拖有很长的尾峰,通常采用的迭代层析成像层析成像算法基本无法完成气体扩散分布的重建。针对气体扩散分布重建面临的不完全投影数据下重建问题,论文首先对传统的层析成像重建算法,特别是迭代层析重建算法,包括代数迭代类算法和统计迭代类算法进行了大量研究,并分析了影响重建质量的各种因素,为不完全投影数据的算法改进提供了理论依据。在此基础之上,论文深入探讨了投影射线扇束构型、双投影方向下的高斯烟羽扩散分布的重建,主要研究工作包括：(1)引入先验矩阵和间隔性使用平滑滤波器的措施,改进了包括：ART、MART、 SART、MLEM等经典迭代重建算法,改进算法对气体扩散的整体峰形、峰值位置以及尾峰等都能够达到较为理想的重建效果。(2)以高斯烟羽模型为测试对象,对改进的迭代重建算法进行了一系列详尽的对比试验,分析射线构型、松弛因子、平滑滤波器的选取、间隔滤波器策略这些因素对迭代重建结果的影响,并进行了改进迭代重建算法的抗噪分析,实验结果表明算法改善了原有重建伪峰严重的问题,具有较强的抗噪性。(3)实现了气体扩散层析成像重建GUI软件,集成多种迭代重建算法,可选择气体扩散分布参数、射线构型以及各类重建判据,方便分析气体扩散分布中各因素对重建的影响以及重建算法对比分析和参数选择。研究结果可以用于光学遥感结合层析成像技术重建污染气体扩散分布信息的理论准备和算法支持,进而为研究气体污染物的大气传输、扩散和沉降过程等科学问题提供依据。
[Abstract]:Iterative tomography algorithm is widely used in the reconstruction of incomplete projection data. Because of the high value of optical instruments, it is not possible to arrange many groups of ray beams to form complex cross light paths due to cost considerations, and most of the gas diffusion has very long tail peaks. In order to solve the problem of gas diffusion distribution reconstruction under incomplete projection data, the traditional tomography reconstruction algorithm is firstly studied in this paper. In particular, iterative tomography reconstruction algorithms, including algebraic iterative algorithms and statistical iterative algorithms, have been studied extensively, and various factors affecting reconstruction quality have been analyzed. This paper provides a theoretical basis for improving the algorithm of incomplete projection data. On this basis, the paper deeply discusses the reconstruction of the distribution of Gao Si plume diffusion in the direction of projection ray fan beam and double projection. The main research work includes the introduction of a prior matrix and the use of smoothing filters at intervals, and the improvement of classical iterative reconstruction algorithms, such as: ARTMARTM, SARTT MLEM, etc., and the improvement of the global peak shape of gas diffusion by the proposed algorithm. Taking Gao Si's smoke plume model as the test object, a series of detailed comparative tests on the improved iterative reconstruction algorithm are carried out to analyze the ray configuration and relaxation factor. The influence of the selection of smooth filter and the strategy of spacer filter on the result of iterative reconstruction is analyzed. The experimental results show that the algorithm improves the serious problem of reconstruction of pseudo peak. The GUI software of gas diffusion tomography reconstruction is implemented, which integrates many iterative reconstruction algorithms. The parameters of gas diffusion distribution, ray configuration and various reconstruction criteria can be selected. It is convenient to analyze the influence of various factors in gas diffusion distribution on reconstruction, contrast analysis and parameter selection of reconstruction algorithm. The results can be used to reconstruct the diffusion distribution information of contaminated gas by optical remote sensing combined with tomography technology. On preparation and algorithm support, It also provides scientific basis for the study of atmospheric transport, diffusion and sedimentation of gas pollutants.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP391.41;TN713

【相似文献】