A Weight Assignment Method for Influencing Factors of Radiographic Digital Images Based on Multiple Regression
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摘要: 针对微焦点射线机检测印制板组装件得到的射线数字图像的客观评价和主观评价不一致的问题，提出一种基于多元回归的数字射线检测图像影响因子的权重分配方法。对影响射线数字图像质量的因素进行分析，选取影响图像质量的各类12种因子，通过模型诊断，剔除t检验不显著的变量，对模型进行改进。得到包括以均值次数、灰度标准差、噪声、失真度、结构相似度、几何放大倍数为变量与主观评价结果为应变量构建的多元回归模型。试验结果表明，该方法得到的图像综合指数与主观评价结果拟合度较高，可以解决主观判别与客观判决不一致的难题，有效避免了人工判别图像质量不客观的弊端。Abstract: In this paper, a new method based on multiple regressions is proposed to determine the weight distribution of the digital ray image. Firstly, the factors that affect the quality of digital ray images are analyzed. Twelve factors which affect the quality of images are selected in this paper. The variables that are not significant in t inspection are eliminated and improved by model diagnosis. Finally, a multivariate regression model, including mean times, gray standard deviation, noise, distortion, structural similarity, geometric magnification being as variables and subjective evaluation results, was constructed. The experimental results show that the composite index of the image obtained by this method is highly fitting with subjective evaluation results. The problems of subjective judgment being inconsistent with objective one were solved. The disadvantages of artificial subjective image quality are effectively avoided.
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