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Spatial sparse scanned imaging based on compressed sensing

机译:基于压缩感测的空间稀疏扫描成像

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A new passive millimeter-wave (PMMW) image acquisition and reconstruction method is proposed based on compressed sensing (CS) and spatial sparse scanned imaging. In this method, the images are sparse sampled through a variety of spatial sparse scanned trajectories, and are reconstructed by using conjugate gradient-total variation recovery algorithm. The principles and applications of CS theories are described, and the influence of the randomness of the measurement matrix on the quality of reconstruction images is studied. Based on the above work, the qualities of the reconstructed images which were obtained by the sparse sampling method were analyzed and compared. The research results show that the proposed method can effectively reduce the image scanned acquisition time and can obtain relatively satisfied reconstructed imaging quality.
机译:基于压缩感测(CS)和空间稀疏扫描成像,提出了一种新的被动毫米波(PMMW)图像采集和重建方法。在该方法中,通过使用共轭梯度 - 总变化恢复算法来重建图像,通过各种空间稀疏扫描轨迹进行稀疏采样。描述了CS理论的原理和应用,研究了测量矩阵的随机性对重建图像质量的影响。基于上述工作,分析并比较了通过稀疏采样方法获得的重建图像的质量。研究结果表明,该方法可以有效地降低图像扫描的采集时间,并且可以获得相对满意的重建成像质量。

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