Feature Analysis and Selection of SAR Image Based on Contourlet Transform

Shi Qi Huang; Pei Feng Su; Yi Ting Wang

doi:10.4028/www.scientific.net/AMM.631-632.431

Paper Titles

Body Recognition Based on Depth Image
p.414

Color Extraction and Research of Image Retrieval Based on Wavelet Territory
p.418

Control Techniques of Class D Audio Power Amplifier
p.422

Design of English Pronunciation Training System for Android
p.427

Feature Analysis and Selection of SAR Image Based on Contourlet Transform
p.431

Image Reconstruction Based on Compressive Sensing via CoSaMP
p.436

Insulator Species Recognition Based on Difference Features of the Color Image
p.441

Online Tracking via Stabilizer and Attractor
p.446

Review of the Key Techniques of Video Velocimetry
p.451

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 631-632Feature Analysis and Selection of SAR Image Based...

Feature Analysis and Selection of SAR Image Based on Contourlet Transform

Abstract:

Synthetic aperture radar (SAR) is a sort of microwave remote sensing imaging radar, which has much advantage. But it also has much shortcoming, such as speckle noise and directional sensitivity. Reducing impact of them to SAR image processing and applications is an important content, especially, extracting features for ground objects. Contourlet transform is a kind of multi-scale and multi-direction transform theory, and it is a sparse representation mode, too. This paper mainly studied Contourlet transform theory and its decomposition structure, and then it was used to extract SAR image features. Experimental results show that Contourlet transform can effetely extract SAR image features.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 631-632)

Pages:

431-435

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.631-632.431

Citation:

Cite this paper

Online since:

September 2014

Authors:

Shi Qi Huang*, Pei Feng Su, Yi Ting Wang

Keywords:

Contourlet Transform, Feature Selection, SAR Image

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] L. X. Wang, L. C. Jiao, X. Y. Yan, F. F. Xin. Change detection in multrtemporal remote sensing images based on the wavelet-domain immune clonal optimazition. Journal of XIAN University (in Chinese), Vol. 40, No. 4 (2013), pp.128-135.

Google Scholar

[2] K. K. Celik Ma. Unsupervised change detection for satellite images using dual-tree complex wavelet transform. IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 3 (2010), p.1199-(2010).

DOI: 10.1109/tgrs.2009.2029095

Google Scholar

[3] M. N. Do, M. Vetterli. Contourlets: a directional multiresolution image representation, International Conference on Image Processing, Vol. 1 (2002), pp.357-360.

DOI: 10.1109/icip.2002.1038034

Google Scholar

[4] M. N. Do, M. Vetterli. The contourlet transform: an efficient directional multiresolution image representation. IEEE Transactions on Image Processing, Vol. 14, No. 12 (2005), pp.2091-2106.

DOI: 10.1109/tip.2005.859376

Google Scholar

[5] J. Li, X. M. Liu, F. L. Xue. Small infrared object detection method based on cycle spinning contourlet transform. Infrared (in Chinese), Vol. 34, No. 2 (2013), pp.39-44.

Google Scholar

[6] X. H. Wand, T. T. Wei, Z. G. Zhou. Remote sensing image fusion method based on the contourlet coefficients correlativity of directional region. Journal of Remote Sensing, Vol. 32, No. 6 (2010), pp.1125-1132.

Google Scholar