This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Complex-valued interferometric inverse synthetic aperture radar (InISAR) image compression is discussed in this study. The target scene has its continuity and is compressible. However, because of the random phase of each resolution cell, the frequency spectrum of an ISAR image is wide and the complex-valued image is hard to compress. A complex-valued ISAR image compression approach is proposed. Using two or more antennas and interferometry processing, the random phase of image pixel can be cancelled and the frequency spectrum becomes sparse. Therefore the theory of compressed sensing can be introduced to the process of the complex-valued image compression. Hence, the complex-valued InISAR image compression and reconstruction can be completed. Results on real data are presented to validate the method. In comparison with results of the conventional compression techniques, the proposed method shows the better ability to preserve both the imaging magnitude and interferometric phase.
References
-
-
1)
-
4. Benz, U., Strodl, K., Moreira, A.: ‘A comparison of several algorithms for SAR raw data compression’, IEEE Trans. Geosci. Remote Sens., 1995, 33, (5), pp. 1266–1276 (doi: 10.1109/36.469491).
-
2)
-
1. Zeng, Z., Cumming, I.G.: ‘SAR image data compression using a tree-structured wavelet transform’, IEEE Trans. Geosci. Remote Sens., 2001, 39, (3), pp. 546–552 (doi: 10.1109/36.911112).
-
3)
-
14. Meng, D., Sethu, V., Ambikairajah, E., Ge, L.: ‘A novel technique for noise reduction in insar images’, IEEE Geosci. Remote Sens. Lett., 2007, 4, (2), pp. 226–230 (doi: 10.1109/LGRS.2006.888845).
-
4)
-
4. Candes, E., Romberg, J., Tao, T.: ‘Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information’, IEEE Trans. Inf. Theory, 2006, 52, pp. 489–509 (doi: 10.1109/TIT.2005.862083).
-
5)
-
6. Baxter, R.A.: ‘SAR image compression with the Gabor transform’, IEEE Trans. Geosci. Remote Sens., 1999, 37, (1), pp. 574–588 (doi: 10.1109/36.739117).
-
6)
-
3. Gergič, B., Planinšič, P., Banjanin, B., et al: ‘A comparison between SAR data compression in Cartesian and polar coordinates’, Int. J. Remote Sens., 2004, 25, (10), pp. 1987–1994 (doi: 10.1080/01431160310001640946).
-
7)
-
7. El Assad, S., Morin, X., Barba, D., Slavova, V.: ‘Compression of polarimetric synthetic aperture radar data’, Prog. Electromagn. Res., 2003, 39, pp. 125–145 (doi: 10.2528/PIER02053002).
-
8)
-
7. Hua, B., Qi, H., Zhang, P., Li, X.: ‘Vector quantization for saturated SAR raw data compression’, Adv. Space Res., 2010, 45, (11), pp. 1330–1337 (doi: 10.1016/j.asr.2010.01.007).
-
9)
-
13. Donoho, D.L.: ‘Compressed sensing’, IEEE Trans. Inf. Theory, 2006, 52, pp. 1289–1306 (doi: 10.1109/TIT.2006.871582).
-
10)
-
2. Candès, E.J., Tao, T.: ‘Decoding by linear programming’, IEEE Trans. Inf. Theory, 2005, 51, (12), pp. 4203–4215 (doi: 10.1109/TIT.2005.858979).
-
11)
-
5. Qiu, X.L., Lei, B., Ge, Y.P., et al: ‘Performance evaluation of two compression methods for SAR raw data’, J. Electron. Inf. Technol., 2010, 32, (9), pp. 2268–2272 (doi: 10.3724/SP.J.1146.2009.01101).
-
12)
-
3. Rosen, A., Hensley, S., Joughin, I.R., et al: ‘Synthetic aperture radar interferometry’, Proc. IEEE, 2000, 99, (3), pp. 333–382 (doi: 10.1109/5.838084).
-
13)
-
E. Candè€s ,
J. Romberg ,
T. Tao
.
Near-optimal signal recovery from random projections: universal encoding strategies?.
IEEE Trans. Inf. Theory
,
2 ,
489 -
509
-
14)
-
P.A. Rosen ,
S. Hensley ,
I.R. Joughin
.
Synthetic aperture radar interferometry.
Proc. IEEE
,
3 ,
333 -
382
-
15)
-
2. Hua, B., Qi, H.M., Zhang, P., Li, X.: ‘Vector quantization for saturated SAR raw data compression’, Adv. Space Res., 2010, 45, pp. 1330–1337 (doi: 10.1016/j.asr.2010.01.007).
-
16)
-
13. Needell, D.: ‘Topics in compressed sensing’, , University of California, CA, USA, , 2009.
-
17)
-
8. McGinley, B., O'Halloran, M., Conceicao, R.C., Higgins, G., Jones, E., Glavin, M.: ‘The effects of compression on ultra wideband radar signals’, Prog. Electromagn. Res., 2011, 117, pp. 51–65.
-
18)
-
3. Gergič, B., Planinšič, P., Banjanin, B., et al: ‘A comparison between SAR data compression in Cartesian and polar coordinates’, Int. J. Remote Sens., 2004, 25, (10), pp. 1987–1994 (doi: 10.1080/01431160310001640946).
-
19)
-
15. Li, L., Li, D., Liu, B., Zhang, Q., Wei, L.: ‘Three-aperture inverse synthetic aperture radar moving targets imaging processing based on compressive sensing’. Proc. ISICT 2012, London, UK, 2012, pp. 210–214.
-
20)
-
7. El Assad, S., Morin, X., Barba, D., Slavova, V.: ‘Compression of polarimetric synthetic aperture radar data’, Prog. Electromagn. Res., 2003, 39, pp. 125–145 (doi: 10.2528/PIER02053002).
-
21)
-
5. Qiu, X.L., Lei, B., Ge, Y.P., et al: ‘Performance evaluation of two compression methods for SAR raw data’, J. Electron. Inf. Technol., 2010, 32, (9), pp. 2268–2272 (doi: 10.3724/SP.J.1146.2009.01101).
-
22)
-
1. Zeng, Z., Cumming, I.G.: ‘SAR image data compression using a tree-structured wavelet transform’, IEEE Trans. Geosci. Remote Sens., 2001, 39, (3), pp. 546–552 (doi: 10.1109/36.911112).
-
23)
-
14. Meng, D., Sethu, V., Ambikairajah, E., Ge, L.: ‘A novel technique for noise reduction in insar images’, IEEE Geosci. Remote Sens. Lett., 2007, 4, (2), pp. 226–230 (doi: 10.1109/LGRS.2006.888845).
-
24)
-
D. Donoho
.
Compressed sensing.
IEEE Trans. Inf. Theory
,
2 ,
1289 -
1306
-
25)
-
E.J. Candes ,
T. Tao
.
Decoding by linear programming.
IEEE Trans. Inf. Theory
,
12 ,
4203 -
4215
-
26)
-
4. Benz, U., Strodl, K., Moreira, A.: ‘A comparison of several algorithms for SAR raw data compression’, IEEE Trans. Geosci. Remote Sens., 1995, 33, (5), pp. 1266–1276 (doi: 10.1109/36.469491).
-
27)
-
6. Baxter, R.A.: ‘SAR image compression with the Gabor transform’, IEEE Trans. Geosci. Remote Sens., 1999, 37, (1), pp. 574–588 (doi: 10.1109/36.739117).
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