Classification of dual- and single polarized SAR images by incorporating visual features

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 90, Issue , 2014, Pages 10-22

  Uhlmann, Stefan ^a   Kiranyaz, Serkan ^a  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

Classification; Color; Image analysis; Synthetic aperture radar; Texture; Visual features

Indexed keywords

CLASSIFICATION (OF INFORMATION); COLOR; IMAGE ANALYSIS; IMAGE CODING; TEXTURES;

CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; LAND-USE AND LAND COVER CLASSIFICATIONS; POLARIMETRIC SAR; POLARIMETRIC SAR DATA; SUPERVISED CLASSIFICATION; TERRAIN CLASSIFICATION; VISUAL FEATURE;

SYNTHETIC APERTURE RADAR;

ACCURACY ASSESSMENT; COLOR; DATA SET; IMAGE ANALYSIS; IMAGE CLASSIFICATION; LAND COVER; POLARIZATION; SYNTHETIC APERTURE RADAR; TERRAIN; VISUAL ANALYSIS;

EID: 84894058457     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2014.01.005     Document Type: Article

References (49)

1. Attema, E., Davidson, M., Snoeij, P., Rommen, B., Floury, N., Agency, E.S., Box, P.O., 2009. SENTINEL-1 Mission Overview. In: Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South, Africa, 12-17 July, pp. 36-39.
2. Aytekin Ö., Koç M., Ulusoy I. Local primitive pattern for the classification of SAR images. IEEE Trans. Geosci. Remote Sens. 2013, 51(4):2431-2441.
3. Chang C.-C., Lin C.-J. Libsvm. ACM Trans. Intell. Syst. Technol. 2011, 2(3):1-27.
4. Cloude S.R., Pottier E. A review of target decomposition theorems in radar polarimetry. IEEE Trans. Geosci. Remote Sens. 1996, 34(2):498-518.
5. Corine Land Cover, 2006. Online: <>. http://sia.eionet.europa.eu/CLC2006/.
6. Cortes C., Vapnik V. Support-vector networks. Machine Learn. 1995, 20(3):273-297.
7. Dai D., Yang W., Sun H. Multilevel Local Pattern Histogram for SAR image classification. IEEE Geosci. Remote Sens. Lett. 2011, 8(2):225-229.
8. Dekker R.J. Texture analysis and classification of ERS SAR images for map updating of urban areas in the netherlands. IEEE Trans. Geosci. Remote Sens. 2003, 41(9):1950-1958.
9. Del Frate, F., Pacifici, F., Solimini, D., 2007. Urban Land Cover in Rome, Italy, monitored by single-parameter multi-temporal SAR images. In: Proc. Urban Remote Sensing Joint Event, Paris. France, 11-13 April, pp. 1-5.
10. Dell'Acqua F., Gamba P. Texture-based characterization of urban environments on satellite SAR images. IEEE Trans. Geosci. Remote Sens. 2003, 41(1):153-159.
11. Deng Q., Chen Y., Zhang W., Yang J. Colorization for Polarimetric SAR Image Based on Scattering Mechanisms 2008, 697-701. Congress on Image and Signal Processing, Sanya, Hainan, China, 27-30 May.
12. De-Yong, H., Xiao-Juan, L., 2008. Texture Analysis and its Application for Single-Band SAR Thematic Information Extraction. In: Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Boston, MA, 6-11 July, pp. 935-938.
13. Ersahin, K., 2004. Incorporating texture information into polarimetric radar classification using neural networks. In: Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Anchorage, AK, 20-24 September, pp. 560-563.
14. Ersahin K., Member S., Cumming I.G., Fellow L., Ward R.K. Segmentation and classification of polarimetric SAR data using spectral graph partitioning. IEEE Trans. Geosci. Remote Sens. 2010, 48(1):164-174.
15. Haralick R.M., Shanmugam K., Dinstein I. Textural features for image classification. IEEE Trans. Syst., Man, and Cybernetics 1973, 3(6):610-621.
16. Hoekman D.H., Vissers M.A.M. A new polarimetric classification approach evaluated for agricultural crops. IEEE Trans. Geosci. Remote Sens. 2003, 41(12):2881-2889.
17. Kandaswamy U., Member S., Adjeroh D.A., Lee M.C. Efficient texture analysis of SAR imagery. IEEE Trans. Geosci. Remote Sens. 2005, 43(9):2075-2083.
18. Kressel U.H.-G. Advances in kernel methods 1999, 255-268. MIT Press, Cambridge, MA, USA. B. Schölkopf, C.J.C. Burges, A.J. Smola (Eds.).
19. Krylov V.A., Moser G., Serpico S.B., Zerubia J. Supervised high-resolution dual-polarization SAR image classification by finite mixtures and copulas. IEEE J. Sel. Top. Signal Process. 2011, 5(3):554-566.
20. Lee J.S., Grunes M. Quantitative comparison of classification capability: fully polarimetric versus dual and single-polarization SAR. IEEE Trans. Geosci. Remote Sens. 2001, 39(11):2343-2351.
21. Lee J.S., Pottier E. Polarimetric Radar Imaging: From Basics to Applications 2009, CRC Press, Taylor & Francis, 397 p.
22. Liew, S., Kam, S., Tuong, T., Chen, P., Minh, V., Lim, H., 1997. Landcover classification over the Mekong river delta using ERS and RADARSAT SAR images. In: Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Singapore, 3-8 August, pp. 2038-2040.
23. Lonnqvist A., Rauste Y., Molinier M., Hame T. Polarimetric SAR data in land cover mapping in boreal zone. IEEE Trans. Geosci. Remote Sens. 2010, 48(10):3652-3662.
24. Lu D., Weng Q. A survey of image classification methods and techniques for improving classification performance. Int. J. Remote Sens. 2007, 28(5):823-870.
25. Manjunath B.S., Wu P., Newsam S., Shin H.D. A texture descriptor for browsing and similarity retrieval. Signal Process.: Image Commun. 2000, 16(1-2):33-43.
26. Manjunath B.S., Ohm J.-R., Vasudevan V.V., Yamada A. Color and texture descriptors. IEEE Trans. Circuits Syst. Video Technol. 2001, 11(6):703-715.
27. Mountrakis G., Im J., Ogole C. Support vector machines in remote sensing: a review. ISPRS J. Photogramm. Remote Sens. 2011, 66(3):247-259.
28. MPEG-7 Part 8, ISO/IEC TR 15938-8). Extraction and use of MPEG-7 descriptions.
29. Partio M., Cramariuc B., Gabbouj M. An ordinal co-occurrence matrix framework for texture retrieval. EURASIP J. Image Video Process. 2007, 2007:1-15.
30. Paudyal, D.R., Eiumnoh, A., Aschbacher, J., 1995. Textural information in SAR images for land-cover applications. In: Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Firenze, Italy, 10-14 July, pp. 1020-1022.
31. Qi Z., Yeh A.G.-O., Li X., Lin Z. A novel algorithm for land use and land cover classification using RADARSAT-2 polarimetric SAR data. Remote Sens. Environ. 2012, 118:21-39.
32. Schistad Solberg A., Jain A.K. Texture fusion and feature selection applied to SAR imagery. IEEE Trans. Geosci. Remote Sens. 1997, 35(2):475-479.
33. Shanmugan K.S., Narayanan V., Frost V.S., Stiles J.A., Holtzman J.C. Textural features for radar image analysis. IEEE Trans. Geosci. Remote Sens. GE 1981, 19(3):153-156.
34. Shimoni M., Borghys D., Heremans R., Perneel C., Acheroy M. Fusion of PolSAR and PolInSAR data for land cover classification. Int. J. Appl. Earth Obs. Geoinf. 2009, 11(3):169-180.
35. Simard M., Saatchi S.S., De Grandi G. The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest. IEEE Trans. Geosci. Remote Sens. 2000, 38(5):2310-2321.
36. Skriver H. Crop classification by multitemporal C-and L-band single-and dual-polarization and fully polarimetric SAR. IEEE Trans. Geosci. Remote Sens. 2012, 50(6):2138-2149.
37. Swain M., Ballard D. Color indexing. Int. J. Comput. Vision 1991, 7(1):11-32.
38. Turkar V., Deo R., Rao Y.S., Mohan S., Das A. Classification accuracy of multi-frequency and multi-polarization SAR images for various land covers. IEEE J. Sel. Top. Appl. Earth Observations Remote Sens. 2012, 5(3):936-941.
39. Uhlmann, S., Kiranyaz, S., 2013. Evaluation of classifiers for polarimetric SAR classification. In: Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, Australia, 21-26 July, pp. 775-778.
40. Ulaby F.T., Kouyate F., Brisco B., Williams T.H.L. Textural information in SAR images. IEEE Trans. Geosci. Remote Sens. 1986, 24(2):235-245.
41. Voisin A., Krylov V., Moser G., Serpico S.B., Zerubia J. Classification of very high resolution SAR images of urban areas using copulas and texture in a hierarchical markov random field model. IEEE Geosci. Remote Sens. Lett. 2013, 10(1):96-100.
42. Wang, P., Hong, W., Cao, F., 2009. Parameters and the hue-saturation based color space models used in the cloude-pottier. In: Proc. IET International Radar Conference, Guilin, China, 20-22 April, pp. 1-4.
43. Yang, W., Zou, T., Dai, D., Shuai, Y., 2009. Supervised land-cover classification of TerraSAR-X imagery over urban areas using extremely randomized clustering forests. In: Proc. Urban Remote Sensing Joint Event, Shanghai, China, 20-22 May, pp. 1-6.
44. Yang, W., Dai, D., Wu, J., He, C., 2010. Weakly supervised polarimetric SAR image classification with multi-modal markov aspect model. In: Proc. ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, 5-7 July, pp. 5-9.
45. Yin H., Cao Y., Sun H. Combining pyramid representation and AdaBoost for urban scene classification using high-resolution synthetic aperture radar images. IET Radar Sonar Navig. 2011, 5(1):58.
46. Yu P., Qin A., Clausi D. Unsupervised polarimetric SAR image segmentation and classification using region growing with edge penalty. IEEE Trans. Geosci. Remote Sens. 2012, 50(4):1302-1317.
47. Zhang L., Zou B., Zhang J., Zhang Y. Classification of polarimetric SAR image based on support vector machine using multiple-component scattering model and texture features. EURASIP J. Adv. Signal Process. 2010, 2010:1-10.
48. Zhou, X., Zhang, C., 2006. A perceptive uniform pseudo-color coding method of SAR images. In: Proc. International Conference on Radar, Shanghai, China, 16-19 October, pp. 1-4.
49. Zou T., Yang W., Dai D., Sun H. Polarimetric SAR image classification using multifeatures combination and extremely randomized clustering forests. EURASIP J. Adv. Signal Process. 2010, 2010:1-10.