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Image Processing
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Optimal Polarization for Contrast Enhancement
in Polarimetric SAR Using Genetic Algorithm
5. Conclusions
Assuming that the polarimetric responses of all the classes in the image are known a priori, determination of polarization states of the transmitter and the receiver for maximizing the contrast ratios between any two classes was presented in this paper. As compared to conventional method, GA shows the ability to provide another and even convenient way to solve optimal polarization problem. It can get all contrast ratios characterizing the best discrimination for any two among all possible classes individually and simultaneously.
It must be emphasized at this point that GA may not always be the best method to deal with all optimal problems in hand, but it has obvious advantage that it seems to find globally optimal solutions without requiring a great deal of information about the solution space. In some sense, it searches for a solution like an engineer learns from experiments and trial-and-error. That makes GA useful for solving problems that were solved experimentally and empirically in the past.
Figure 1.Flow diagram of GA
Figure 2. L-band SAR image of the San Francisco
| Polarization/class |
Urban/Ocean |
Park/Ocean |
Urban/Park |
| Optimal- Lagrange |
28.5990 dB |
19.1451 dB |
9.5674 dB |
| Optimal-GA |
28.5988 dB |
19.1449 dB |
9.5674 dB |
| Linear-HH |
15.1013 dB |
7.3075 dB |
7.7938 dB |
| Linear-HV |
20.3604 dB |
17.2547 dB |
3.1057 dB |
| Linear-VV |
9.4340 dB |
4.2362 dB |
5.1978 dB |
| GA(simultaneously) |
28.5988 dB |
19.0547 dB |
9.5441 dB |
Table 1. contrast ratios for different polarizations.
Table 2. Polarization angles and solution chromosome for simultaneous case
6. Reference
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A. A. Swartz, H. A. Yueh, J. A. Kong, L. M. Novak, and R. T. Shin, "Optimal polarizations for achieving maximum contrast in radar images," J. Geophys. Res.,93, pp.15252-15260, 1987
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- J. G. Teti, Jr., F. J. llsemann, J. S. Verdi, W.-M. Boerner, and S. K. Krasznay, "Application of the Polarimetric Matched Image Filter to the Assessment of SAR Data from the Mississippi Flood Region," Geoscience and Remote Sensing Symposium, Vol. 3, pp.1368 -1370, 1994
- Jian Yang, Yoshio Yamaguchi, Wolfgang-Martin Boerner, and Shiming Lin, "Numerical Methods for solving the Optimal Problem of Contrast Enhancement," IEEE Transactions on Geoscience and Remote Sensing, Vol. 38, No. 2, pp.965-971, 2000
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- Randy L. Haupt, "An Introduction to Genetic Algorithm for Electromagnetics," IEEE Antennas and Propagation Magazine, Vol.37, No.2, pp.7-15, 1995
- Eric A. Jones and William T. Jones, "Design of Yagi-Uda Antennas Using Genetic Algorithms," IEEE Transactions on Antennas and Propagation, Vol. 45, No. 9, pp.1386-1392, 1997
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