基于小波变换的独立分量分析及其在红外热波图像中的应用

基金项目:

国家自然科学基金资助项目《SRM壳体多层结构热波传导特性及缺陷定量识别方法研究》(51075390)

详细信息

ICA Based Wavelet Transform and its Application to Infrared Thermal Wave Image

摘要: 针对获取的红外热波图像存在加热不均、信噪比小、对比度低的特点，提出基于小波变换的独立分量分析法并将其应用于红外热波图像处理，该方法首先对红外图像进行小波分解，提取高频分量构建虚拟噪声通道，进而提高独立分量分析方法消噪性能。试验结果表明，该方法可以达到很好的消噪效果，使图像的缺陷显示更为清晰。
- 独立分量分析 /
- 小波变换 /
- 红外图像处理 /
- 虚拟噪声通道
Abstract: Aiming at the problems that the thermal wave image is subjected with the uneven heating, low signal-to-noise ratio and low defect contrast of the image, the paper proposes a kind of new ICA method based on wavelet transform and its application to the thermal wave image processing. The concept of virtual noise channel was introduced from high frequency component by wavelet transform and used to improve the performance in signal de-noising of ICA. The experiments indicate that good de-noised results can be obtained and the display of defects can be seen clearly with the method.
- ICA /
- Wavelet transform /
- Infrared image processing /
- Virtual noise channel

[1]	王迅，金万平，张存林，等.红外热波无损检测技术及其进展［J］.无损检测,2004,26(10):497-501.
[2]	Xavier P V. Nondestructive Testing Handbook. Third Edition. Infrared and Thermal Testing［M］. USA: Columbus American Society for Nondestructive Testing,2001.
[3]	赖睿，刘上乾，王炳键，等.一种新的自适应红外图像增强算法［J］.半导体光电,2006,27(6):767-769.
[4]	闫记香.基于小波变换的红外图像序列增强［D］.西安：西安电子科技大学,2008.
[5]	季忠，金涛，杨炯明等.虚拟噪声通道在基于ICA消噪过程中的应用［J］.中国机械工程,2005,16(4):350-353.
[6]	郭兴旺，邵威，郭广平.红外无损检测加热不均时的图像处理方法［J］.北京航空航天大学学报,2005,31(11):1204-1207.
[7]	王爱玲，叶明生，邓秋香，等.图像处理技术与应用［M］.北京：电子工业出版社,2008:243-257.
[8]	Hyvrinen A, Oja E, Hoyer P, et al. Image feature extraction by sparse coding and independent component analysis ［C］. Proc Int Conf on Pattern Recognition, Brisbane Australia:1998.
[9]	Chen C H, Wang X J. A novel theory of SAR image restoration and enhancement with ICA［C］. IEEE Geoscience and Romote Sensing Symposium, Anchorage, America:2004.