基于小波变换的红外热波无损检测融合算法

在红外热波无损检测中获取的热像序列存在着背景噪声大、缺陷边缘模糊、对比度低等特点。为了提高由红外热像序列重构的数字图像的缺陷显示能力,以小波变换为热像处理工具,采用基于像素级和特征级的图像融合算法对热像序列进行了处理,并采用基于统计学的图像评估标准对处理效果作了定量评价。通过对铝合金试件的检测实验说明该方法可用于材料内部缺陷的红外热波无损检测。研究结果表明,此种图像融合算法可对不同深度缺陷所对应的两幅最佳热像进行有效地融合,在一幅融合图像中直观地反映出全部缺陷,并能有效地减少加热不均和背景噪声对缺陷识别的不利影响。

An image fusion algorithm based on wavelet transform used in infrared thermal wave nondestructive testing

The quality of infrared image sequence acquired in infrared thermal wave nondestructive testing(NDT) is usually poor because of its high background noise,blurred defect edges and low contrast.To improve the defect display capability of the digital image reconstructed from infrared image sequence,an image fusion algorithm by wavelet transform based on pixel level and characteristic level is introduced,and the processing effects are evaluated quantitatively by a statistical standard of image evaluation.It is illustrated by the test of aluminium alloy sample that the algorithm is acceptable in infrared thermal wave NDT of internal defects in materials.It is shown that the algorithm of image fusion is effective for the two best infrared images corresponding to defects at different depth,all the defects can be directly reflected in one fusion image,and the uneven heating effect and background noise are suppressed effectively.