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Compressed sensing sparse reconstruction for coherent field imaging

Compressed sensing sparse reconstruction for coherent field imaging
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摘要 Return signal processing and reconstruction plays a pivotal role in coherent field imaging, having a significant in- fluence on the quality of the reconstructed image. To reduce the required samples and accelerate the sampling process, we propose a genuine sparse reconstruction scheme based on compressed sensing theory. By analyzing the sparsity of the received signal in the Fourier spectrum domain, we accomplish an effective random projection and then reconstruct the return signal from as little as 10% of traditional samples, finally acquiring the target image precisely. The results of the numerical simulations and practical experiments verify the correctness of the proposed method, providing an efficient processing approach for imaging fast-moving targets in the future. Return signal processing and reconstruction plays a pivotal role in coherent field imaging, having a significant in- fluence on the quality of the reconstructed image. To reduce the required samples and accelerate the sampling process, we propose a genuine sparse reconstruction scheme based on compressed sensing theory. By analyzing the sparsity of the received signal in the Fourier spectrum domain, we accomplish an effective random projection and then reconstruct the return signal from as little as 10% of traditional samples, finally acquiring the target image precisely. The results of the numerical simulations and practical experiments verify the correctness of the proposed method, providing an efficient processing approach for imaging fast-moving targets in the future.
出处 《Chinese Physics B》 SCIE EI CAS CSCD 2016年第4期79-84,共6页 中国物理B(英文版)
基金 supported by the National Natural Science Foundation of China(Grant No.61505248) the Fund from Chinese Academy of Sciences,the Light of"Western"Talent Cultivation Plan"Dr.Western Fund Project"(Grant No.Y429621213)
关键词 coherent field imaging computational imaging sparse reconstruction compressed sensing coherent field imaging, computational imaging, sparse reconstruction, compressed sensing
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