Research on Super Resolution Algorithms Applied in Ultrasonic Image Based on Combining Wavelet with Interpolation
摘 要
针对超声图像分辨率较低的缺点, 对现有基于小波和插值的图像放大方法进行归纳、总结和分析, 提出了一种基于小波和插值的超分辨率图像处理方法, 该方法选择合适的小波与插值的结合方式, 采用基于区域能量的判定方法, 通过适当减少低频子带的比例同时尽可能多地恢复高频子带的方法重建超分辨率图像。通过5种方法对超声图像进行对比试验, 结果表明: 第5种该方法能有效地提高超声图像的分辨率, 对材料感兴趣区域的缺陷检测可起到“探针”作用。
Abstract
Aiming at the lower resolution of ultrasound image characteristics, the existing image zooming methods based on wavelet and interpolation are summarized and analyzed, on the basis of which super-resolution image processing algorithm based on wavelet and interpolation was proposed. In the algorithm, the first step is to choose a suitable combination of wavelet and interpolation, and then to use the energy determination method based on region energy. The final step is to reconstruct a super-resolution image through properly reducing wavelet low-frequency band at the same time as much as possible restoring high-frequency band. Through contrast experiments on a single static ultrasound image by five methods, the results showed that the method can effectively improve the resolution of ultrasound images, and could play “probe” role for defect detection in an interested region of material.
中图分类号 TG115.28
所属栏目 科研成果与学术交流
基金项目 广东省自然科学基金资助项目(07006479); 广东省重点攻关项目(2006B12401001)
收稿日期 2008/2/25
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备注戴光智(1974-), 男, 讲师, 博士, 主要从事焊缝超声无损检测及信号处理等的研究。
引用该论文: DAI Guang-Zhi,CHEN Tie-Qun,QIU Dong-Mei. Research on Super Resolution Algorithms Applied in Ultrasonic Image Based on Combining Wavelet with Interpolation[J]. Nondestructive Testing, 2009, 31(4): 251~255
戴光智,陈铁群,邱栋美. 小波和插值结合应用于超声图像的超分辨率算法[J]. 无损检测, 2009, 31(4): 251~255
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参考文献
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【2】Ford C, Etter D M. Wavelet basis reconstruction of nonuniformlv sampled data[J]. IEEE Transactions on Circuits and Systems II: analog, Digital Signal Processing,1998,45(8): 1165-1168.
【3】Nhat Nguyen, Peyman Milanfar. Wave1et-based interpolation restoration method for superresolution(wavelet superresolution)[J]. Circuits Systems Signal Process,2000,19(4): 321-338.
【4】Nguyen N. Numerical techniques for image super resolution[D]. USA: Stanford University,2000.
【5】Bose N K, Lertrattanapanich S. Advance in wavelet superresolution[C]. SAMPTA Proceeding of International Conference on Sampling Theory and Application,2001: 13-17.
【6】冯 若, 刘忠奇, 姚锦钟, 等.超声诊断设备原理与设计[M].北京: 中国医药科技出版社,1993.
【7】Akay M. Time Frequency and Wavelets in Biomedical Signal Processing[M]. Piscataway, NJ: IEEE Press,1998.
【8】Papadimitriou S, Bezerianos A. Nonlinear analysis of the performance and reliability of wavelet singularity detection based denoising for Doppler ultrasound fetal heart rate signals[J]. Int J Med Inf,1999,53: 43-60.
【9】Abbate A, Koay J, Frankel J, et al. Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection[J]. IEEE Trans UFFC,1997,44(1): 14-25.
【10】Polikar R, Udpa L. Frequency invariant classification of ultrasonic weld inspection signals[J]. IEEE Trans UFFC,1998,45(3): 614-625.
【11】Robini M C, Magnin I E, Benoit H, et a1. Two-dimensional ultrasonic flaw detection based on the wavelet packet transform[J]. IEEE Trans UFFC,1997,44(6): 1382-1394.
【12】张广明, 马宏伟.超声无损检测中的缺陷识别与噪声抑制[J].中国机械工程,1999,10(12): 1389-1391.
【13】马国强,郭宝龙,玛宗哲.传输图像的子波域插值恢复算法[J].电子学报,2002,(4): 552-555.
【14】郝鹏威, 朱重光.基于小波的图像插值方法[J].遥感学报,1998,2(2): 98-102.
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