ABSTRACT In indoor applications, computed tomography is the process of transforming a network of intersecting attenuation measurements into a spatially resolved two-dimensional concentration map. In this study the Low Third Derivative method (LTD) was numerically evaluated and optimized for different conditions. A modified version of the LTD algorithm (LTDm) was proposed and evaluated against the original version. Eight test maps were reconstructed under different conditions, such as weight ratio, pixel resolution, beam density and measurement noise. Performance of both LTD algorithms was found to be intimately related to the number of peaks and complexity in the test map and the steepness of the peaks. The LTDm algorithm improved the quality, especially for concentration maps including steep gradients and regions with very low concentrations. The LTDm method heavily lessened aliasing distortions and efficiently minimized the effects of noise.

中文翻译：

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使用改进的低三阶导数法绘制示踪气体浓度图：数值研究

摘要 在室内应用中，计算机断层扫描是将交叉衰减测量网络转换为空间分辨二维浓度图的过程。在本研究中，对不同条件下的低三阶导数方法 (LTD) 进行了数值评估和优化。提出了 LTD 算法 (LTDm) 的修改版本，并针对原始版本进行了评估。在重量比、像素分辨率、光束密度和测量噪声等不同条件下重建了八张测试图。发现两种 LTD 算法的性能与测试图中的峰值数量和复杂性以及峰值的陡度密切相关。LTDm 算法提高了质量，特别是对于包括陡峭梯度和非常低浓度区域的浓度图。