基于卡通-纹理模型的激光吸收光谱层析成像  

Laser Absorption Spectroscopy Tomography Based on Cartoon-TextureModel

作　　者：司菁菁[1,4] 吕东灿 张瑞 程银波 刘畅 Si Jingjing;LüDongcan;Zhang Rui;Cheng Yinbo;Liu Chang(School of Information Science and Engineering,Yanshan University,Qinhuangdao 066004,Hebei,China;Ocean College,Hebei Agricultural University,Qinhuangdao 066003,Hebei,China;School of Engineering,the University of Edinburgh,Edinburgh EH93JL,UK;Hebei Key Laboratory of Information Transmission and Signal Processing,Qinhuangdao 066004,Hebei,China)

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004 [2]河北农业大学海洋学院,河北秦皇岛066003 [3]爱丁堡大学工程学院,英国爱丁堡EH93JL [4]河北省信息传输与信号处理重点实验室,河北秦皇岛066004

出　　处：《中国激光》2024年第6期220-230,共11页Chinese Journal of Lasers

基　　金：国家自然科学基金(62371415);河北省自然科学基金(F2021203027);河北省重点实验室项目(202250701010046);燕山大学基础创新科研培育项目(2021LGZD011)。

摘　　要：可调谐二极管激光吸收光谱层析成像(TDLAT)是一种重要的光学非侵入式燃烧检测技术。然而,TDLAT逆问题的欠定性本质使得现有迭代层析成像算法重建的燃烧场温度分布图像存在较大误差。针对该问题,笔者将图像处理领域的卡通-纹理模型引入TDLAT,提出了基于卡通-纹理模型的温度重建算法(TRACT)。该算法利用全变差约束下的Landweber算法重建气体吸收密度图像中的卡通成分,较好地恢复其中的平滑特征与边缘结构;构建改进的迭代收缩阈值算法深度展开网络,并用其重建气体吸收密度图像中的细节纹理成分;通过卡通成分重建与纹理成分重建的相互补充,提高气体吸收密度图像的整体重建质量,进而提高燃烧场温度分布图像的重建质量。利用火焰动力学模拟器生成的仿真数据与利用TDLAT实验系统实际测量数据进行的重建实验均表明,与现有的迭代层析成像算法相比,TRACT重建的燃烧场温度分布图像在客观评价指标与主观视觉质量方面均有较大提升。Objective Tunable diode laser absorption spectroscopy tomography(TDLAT)is an important optical noninvasive combustion detection technique.Two-line thermometry is widely used in TDLAT for temperature imaging,in which the absorbance density distributions for two spectral transitions with different temperature-dependent line strengths are individually reconstructed,and the temperature image is then retrieved from the ratio of the absorbances in each pixel of the region of interest.Owing to the limited number of available line-of-sight TDLAT measurements in practical applications,the inverse problem of reconstructing the absorbance density distribution is inherently ill-posed,leading to severe artifacts in the reconstructed temperature image.To alleviate this problem,iterative tomographic algorithms have been proposed by formulating an inverse problem with a heuristically determined prior,such as the smoothness of absorbance density distributions.These algorithms improve the quality of the reconstructed smooth characteristics in temperature images to some degree;however,the lack of detailed features in the reconstructed image is evident.To address this problem,a cartoon-texture model in the field of image processing is introduced into TDLAT,and the temperature reconstruction algorithm based on the cartoon-texture model(TRACT)is proposed.Methods The proposed TRACT individually reconstructs the cartoon and textural components of the absorbance density distribution with smoothness and sparsity priors,and retrieves the temperature image with two-line thermometry from the combination of the reconstructed cartoon and texture components.First,the cartoon component is reconstructed using the total variation(TV)regularized Landweber algorithm(Landweber-TV)to effectively retrieve the smooth characteristics and edge structure in the absorbance density distribution.Second,the texture component is reconstructed with a modified deep network unfolded using the iterative shrinkage-thresholding algorithm(ISTA-mNet)to supplement the d

关 键 词：光谱学 可调谐二极管激光吸收光谱 层析成像 温度重建 双线测温法 卡通-纹理模型 

分 类 号：O433.1[机械工程—光学工程]