Binbing Li

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For synthetic aperture radar (SAR) systems, high data rate is generally needed to achieve high-resolution of two dimension images, which leads to the huge amount of data storage. In the framework of compressive sensing theory, the compressibility of the signal makes it possible to reconstruct the signal from significantly reduced number of samples. And the(More)
Signal models such as wavelet trees, block sparsity and statistical models are integrated into compressed sensing (CS) recovery algorithms in order to improve recovery accuracy and decrease the number of measurements. However, there are many constraints in practical applications. This paper introduces a new simple and efficient model based on the fact that(More)
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