Open AccessComplex‐valued interferometric inverse synthetic aperture radar image compression base on compressed sensing
Author(s) -
Li Liechen,
Li Daojing,
Liu Bo,
Zhang Qingjuan
Publication year - 2014
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2014.0033
Subject(s) - computer science , inverse synthetic aperture radar , computer vision , interferometry , artificial intelligence , synthetic aperture radar , image compression , radar imaging , compression (physics) , data compression , compressed sensing , phase (matter) , radar , image (mathematics) , algorithm , optics , image processing , physics , telecommunications , quantum mechanics , thermodynamics
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.