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首页> 外文期刊>Radiation Physics and Chemistry >Defect detections in industrial radiography images by a multi-scale LMMSE estimation scheme
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Defect detections in industrial radiography images by a multi-scale LMMSE estimation scheme

机译:通过多尺度LMMSE估计方案缺陷工业造影图像中的缺陷检测

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摘要

The defect detection of welded objects is at the core of nondestructive testing and has found many applications in many industries. Industrial radiography is widely used for inspection of welded objects. In the low contrast radiography, image processing can assist to improve image quality. In this paper, an interlaced over complete wavelet expansion (OWE) and linear minimum mean square error estimation (LMMSE) are implemented to detect defects and improve the contrast of industrial radiography images. In the first stage, OWE is implemented to the radiograph and the wavelet coefficients can be calculated. Then, LMMSE can be applied to calculate the threshold level of each scale and the new wavelet coefficient. Finally, to reconstruct the output image, an inverse OWE transform will be applied. The experimental results show that the reconstructed images have higher contrast than the original radiograph in the defect regions.
机译:焊接物体的缺陷检测是非破坏性测试的核心,并在许多行业中发现了许多应用。 工业造影广泛用于检查焊接物体。 在低对比度射线照相中,图像处理可以有助于提高图像质量。 在本文中,实现了完全小波膨胀(欠款)和线性最小均方误差估计(LMMSE)的交错来检测缺陷并改善工业造影图像的对比度。 在第一阶段,欠欠实现到射线照片,并且可以计算小波系数。 然后,可以应用LMMSE来计算每个比例的阈值水平和新的小波系数。 最后,要重建输出图像,将应用反向欠换变换。 实验结果表明,重建的图像比缺陷区域中的原始射线照片具有更高的对比度。

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