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Study on the algorithm of computational ghost imaging based on discrete fourier transform measurement matrix

机译:基于离散傅里叶变换测量矩阵的计算重​​影成像算法研究

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摘要

On the basis of analyzing the cosine light field with determined analytic expression and the pseudo-inverse method, the object is illuminated by a presetting light field with a determined discrete Fourier transform measurement matrix, and the object image is reconstructed by the pseudo-inverse method. The analytic expression of the algorithm of computational ghost imaging based on discrete Fourier transform measurement matrix is deduced theoretically, and compared with the algorithm of compressive computational ghost imaging based on random measurement matrix. The reconstruction process and the reconstruction error are analyzed. On this basis, the simulation is done to verify the theoretical analysis. When the sampling measurement number is similar to the number of object pixel, the rank of discrete Fourier transform matrix is the same as the one of the random measurement matrix, the PSNR of the reconstruction image of FGI algorithm and PGI algorithm are similar, the reconstruction error of the traditional CGI algorithm is lower than that of reconstruction image based on FGI algorithm and PGI algorithm. As the decreasing of the number of sampling measurement, the PSNR of reconstruction image based on FGI algorithm decreases slowly, and the PSNR of reconstruction image based on PGI algorithm and CGI algorithm decreases sharply. The reconstruction time of FGI algorithm is lower than that of other algorithms and is not affected by the number of sampling measurement. The FGI algorithm can effectively filter out the random white noise through a low-pass filter and realize the reconstruction denoising which has a higher denoising capability than that of the CGI algorithm. The FGI algorithm can improve the reconstruction accuracy and the reconstruction speed of computational ghost imaging.
机译:在利用确定的解析表达式分析余弦光场和伪逆方法的基础上,通过具有确定的离散傅里叶变换测量矩阵的预设光场对物体进行照明,并通过伪逆方法重建物体图像。 。从理论上推导了基于离散傅里叶变换测量矩阵的计算重​​影成像算法的解析表达式,并与基于随机测量矩阵的压缩计算重影成像算法进行了比较。分析了重建过程和重建误差。在此基础上,进行仿真以验证理论分析。当采样测量次数与目标像素数目相似时,离散傅里叶变换矩阵的秩与随机测量矩阵之一相同,FGI算法和PGI算法的重建图像的PSNR相似,重建传统的CGI算法的误差要小于基于FGI算法和PGI算法的重建图像。随着采样次数的减少,基于FGI算法的重建图像的PSNR缓慢下降,基于PGI算法和CGI算法的重建图像的PSNR急剧下降。 FGI算法的重构时间比其他算法要短,并且不受采样测量次数的影响。 FGI算法可以通过低通滤波器有效地滤除随机白噪声,实现比CGI算法具有更高去噪能力的重构去噪。 FGI算法可以提高计算重影成像的重建精度和重建速度。

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