Turbine blade DR images fusion based on bi-energy X-ray radiography
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摘要: 为了提高单帧涡轮叶片DR(Digital Radiography)图像的信息量,首先在2个不同射线能量下对涡轮叶片进行DR成像,以获取不同厚度区域的质量信息;然后将2幅DR图像进行多分辨率小波分解,以最大局部方差为准则对二者的低频子带图像进行融合,以局部梯度的活性因子为尺度对二者的高频子带图像进行融合;最后基于小波融合系数的逆变换获得最终的融合结果.实验结果表明:基于此方法的涡轮叶片融合DR图像携带了更为丰富的细节信息,从而有利于叶片质量信息的快速、准确判读.Abstract: In order to increase the single frame digital radiography(DR) image information of the turbine blade, two DR images were captured at different X-ray energy so as to get the turbine blade quality information at different thickness region firstly. Secondly, the two original DR images were decomposed by wavelet transform, and the maximal local variance role was used to carry out the low sub-frequenced image fusion, and the active factors based on local gradients were calculated to carry out the high sub-frequenced image fusion. Finally, through inverse wavelet transform the output image can be obtained. The experimental results show that the single frame fused turbine blade DR image brings more detailed information, so it is useful to the fast and accurate quality judgements of the turbine blade.
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Key words:
- turbine blade /
- X-ray testing /
- digital radiography(DR) image fusion /
- wavelet transform
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