Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

2.10

CiteScore

Chi-Hau Chen This email address is being protected from spambots. You need JavaScript enabled to view it.1 and Uvais Qidwai This email address is being protected from spambots. You need JavaScript enabled to view it.2

1ECE Department University of Massachusetts, Dartmouth Massachusetts, U.S.A.
2EECS Department Tulane University, New Orleans, Louisiana, U.S.A. 


 

Received: October 25, 2001
Accepted: February 19, 2002
Publication Date: March 1, 2002

Download Citation: ||https://doi.org/10.6180/jase.2002.5.1.06  


ABSTRACT


Ultrasonic imaging for nondestructive evaluation (NDE) applications is an important process for industrial applications. Understanding the material structure is an integral part of the manufacturing as well as maintenance operations. Especially for the critical industries like airlines where each component of the aircraft is required to perform at its best. One way to analyze material samples for defects is to take its x-ray image. This method is not only hazardous but also highly impractical to be used in many industrial applications specially during running conditions of structures. In addition, it is also very costly procedure. Ultrasonic imaging is an alternate for such application and is constantly gaining popularity in the industrial applications. Ultrasonic images are constrained by the sensor positions and indirect image formation. In this paper, some recent techniques in the areas of ultrasonic image enhancement and restoration, developed by the authors, are presented. Three new approaches have been presented to enhance the ultrasonic images with minimum or no information of the distortion function or the imaging system characteristics.


Keywords: Ultrasonic Images, Nondestructive Evaluation, H-Infinity Method, High-Order Statistics Algorithms, 2D-Deconvolution, Image Restoration


REFERENCES


  1. [1] Du, C., Xie, L. and Soh, Y. C., “Robust H∞ Filtering of Uncertain 2-D Discrete Systems,” Proceedings of the American Control Conference, pp. 4423-4427 (1999).
  2. [2] Du, C., Xie, L. and Soh, Y. C., “H∞ State Estimation of 2-D Discrete Systems,” Proceedings of the American Control Conference, pp. 4429-4432 (1999).
  3. [3] Fornasini, E. and Marchesini, “Doubly Indexed Dynamical Systems: State-Space Models and Structural Properties,” Mathematical System Theory, Vol. 12, pp. 1313-1316 (1978).
  4. [4] Gonzales, R. C. and Woods, R. E., Digital Image Processing, Addison-Wesley Publishing Company, New York, U.S.A., pp. 413-465 (1992).
  5. [5] MATLAB Image Processing Toolbox.
  6. [6] Overschee, P. and Moor, B., Subspace Identification for Linear Systems, Kluwer Academic Publishers, Boston, U.S.A. (1996).
  7. [7] Qidwai, U., “2D Blind Deconvolution for Image Enhancement with Applications to Ultrasonic NDE,” Ph.D.Thesis, University of Massachusetts Dartmouth, U.S.A. (2001).
  8. [8] Qidwai, U. and Chen, C. H., “Blind Enhancement for Ultrasonic C-Scans Using Recursive 2-D H-Based State Estimation and Filtering,” INSIGHT, Journal of British Institute of Nondestructive Testing, Vol. 42, pp. 737-741 (2000).
  9. [9] Qidwai, U. and Chen, C. H., “Blind-H Deconvolution for Ultrasonic C-Scans:1-D Approach,” Journal of NDE, Vol. 21, pp. 40-46 (2001).
  10. [10] Qidwai, U. and Chen, C. H., “Hybrid 2D-H-Based Blind Enhancement for Ultrasonic C-Scans”, Proceedings of the 39th Annual Conference of British Institute of Non Destructive Testing, at Buxton, U.K., pp. 137-142 (2000).
  11. [11] Qidwai, U. and Chen, C. H., “Blind Image-Deconvolution for Ultrasonic C-Scans,” Review of the Progress in Quantitaive Nondestructive Evaluation (RQNDE), Iowa, U.S.A. (2000).
  12. [12] Qidwai, U. and Chen, C. H., “C-Scan Using Constrained 2D-HOS,” Blind Image Restoration for Ultrasonic, ICASSP, Utah-USA, (2001).
  13. [13] Qidwai, U. and Chen, C. H., “Blind Image Restoration for Ultrasonic C-Scan Using Constrained 4th Order Cumulamnts,” ASME Congress, New York, U.S.A. (2001).
  14. [14] Qidwai, U. and Chen, C. H., “C-Scan Enhancement Using Recursive Subspace Deconvolution”, Review of the Progress in Quantitaive Nondestructive Evaluation (RQNDE), Maine, U.S.A. (2001).
  15. [15] Šebek, M., “H∞ Problem of 2-D Systems,” European Control Conference, pp. 1476-1479 (1993).
  16. [16] Shaked U. and Theodor Y., “H∞ Optimal Estimation: A Tutorial,” Proceedings of the IEEE-Conference on Decision and Control, pp. 2278-2286 (1992).
  17. [17] Zames, G., “Feedback and Optimal Sensitivity: Model Reference Transformation, Multiplicative Seminorms, and Approximate Inverse,” IEEE Transactions on Automatic Control, Vol. 23, pp. 301-320 (1981).