DocumentCode :
576035
Title :
Blocked spectrum compressive sensing based on Root-MUSIC algorithm for SAR image
Author :
Li, Xiaobo ; Chen, Jie ; Zhu, Yanqing
Author_Institution :
Sch. of Electron. Inf. Eng., Beihang Univ., Beijing, China
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
2094
Lastpage :
2096
Abstract :
In order to effectively reduce the storage volume of complex image data in high-resolution synthetic aperture radar (SAR), blocked spectrum compressive framework [1][2] based on Root-MUSIC algorithm is proposed. In this paper block-wise processing [3] of SAR image method is introduced, which can effectively reduce the storage space of measurement matrix. Gaussian random matrix is employed as observation matrix [4][5] to obtain observed value of each sub-block. Model parameters can be calculated by means of Root-MUSIC algorithm. Spectrum signal is reconstructed from small amount of measurements. Simulation results with real spatial-sparse SAR image demonstrate that data storage capacity can be reduced to as low as 1.17%, which validate the effectiveness of the method.
Keywords :
Gaussian processes; compressed sensing; image reconstruction; matrix algebra; radar imaging; synthetic aperture radar; Gaussian random matrix; SAR image method; block-wise processing; blocked spectrum compressive sensing; data storage capacity reduction; high-resolution synthetic aperture radar; measurement matrix; observation matrix; root-MUSIC algorithm; spatial-sparse SAR image; spectrum signal reconstruction; storage volume reduction; Compressed sensing; Discrete cosine transforms; Frequency domain analysis; Image reconstruction; Signal processing algorithms; Sparse matrices; Synthetic aperture radar; SAR image; block; compressive sensing; root-music algorithm; signal reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6350959
Filename :
6350959
Link To Document :
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