volume | PIER Journals

Abstract

In order to ensure that SAR scene matching aided navigation system can acquire the position errors and yawing errors simultaneously, we propose an image matching algorithm based on Scale Invariant Feature Transform (SIFT). However, the SIFT is proposed for optical image, and its performance degrades when used in SAR image. To enhance the adaptability of SIFT, two ways are employed. One is the application of a preprocessing on image pairs before matching. The other is the establishment of a scale and rotation restriction criteria on tie-points after SIFT matching. Compared with other matching methods, experiment results show that the proposed method is much more suitable for SAR image and successes in matching performance improvement. Furthermore, the method can meet the real-time requirement.

1. James, E. B. and A. M. Charles, "Precision aided inertial navigation using SAR and digital map data," IEEE Position Location and Navigation Symposium, 490-496, Las Vegas, NV, USA, 1990. Google Scholar

2. Sheng, Y. W. and D. E. Alsdorf, "Automated georeferencing and orthorectification fo Amazon basin-wide SAR mosaics using SRTM DEM data," IEEE Trans. Geosci. Remote Sens., Vol. 43, No. 8, 1929-1940, 2005.
doi:10.1109/TGRS.2005.852160 Google Scholar

3. Mikolajczyk, K. and C. Schmid, "An affne invariant interest point detector," ECCV 2002, 128-142, Berlin Heidelberg, Germany, 2002. Google Scholar

4. Mikolajczyk, K. and C. Schmid, "A performance evaluation of local descriptors," IEEE Trans. Pattern Anal. Mach. Intell., Vol. 27, No. 10, 1615-1630, 2005.
doi:10.1109/TPAMI.2005.188 Google Scholar

5. Lowe, D., "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., Vol. 60, 91-110, 2004.
doi:10.1023/B:VISI.0000029664.99615.94 Google Scholar

6. Grabner, M., H. Grabner, and H. Bischof, "Fast approximated SIFT," Asian Conferonce on Comput. Vis., 918-927, Hyderabad, India, 2006. Google Scholar

7. Ke, Y. and R. Sukthankar, "PCA-SIFT: A more distinctive representation for local image descriptors," Proceedings of IEEE Comput. Soci. Conference on Comput. Vis. Pattern. Recog., 506-513, Washington D.C., USA, 2004. Google Scholar

8. Lu, J., B. Wang, H. M. Gao, and Z. Q. Zhou, "SAR images matching based on local shape descriptors," IET International Radar Conference, 235-238, Guilin, China, 2009. Google Scholar

9. Yi, Z., Z. G. Cao, and X. Yang, "Multi-spectral remote image registration based on SIFT," Electron. Lett., Vol. 44, No. 2, 107-108, 2008.
doi:10.1049/el:20082477 Google Scholar

10. Bastanlar, Y., A. Temizel, and Y. Yardimci, "Improved SIFT matching for image pairs with scale difference," Electron. Lett., Vol. 46, No. 5, 346-348, 2010.
doi:10.1049/el.2010.2548 Google Scholar

11. Xie, H., L. Pierce, and F. Ulaby, "Statistical properties of logarithmically transformed speckle," IEEE Trans. Geosci. Remote Sens., Vol. 40, No. 3, 721-727, 2002.
doi:10.1109/TGRS.2002.1000333 Google Scholar

12. Xie, H., L. Pierce, and F. Ulaby, "SAR speckle reduction using wavelet denoising and Markov random filed modeling," IEEE Trans. Geosci. Remote Sens., Vol. 40, No. 10, 2196-2212, 2002.
doi:10.1109/TGRS.2002.802473 Google Scholar

13. James, E. B. and A. M. Charles, "Precision aided inertial navigation using SAR and digital map data," IEEE Position Location and Navigation Symposium, 490-496, Las Vegas, NV, USA, 1990. Google Scholar

Dr. Sanhai Ren

Dr. Wenge Chang

Dr. Xiangjun Liu