为了消除背景光强动态变化引起的非线性误差,提出了基于压缩感知成像系统的动态背景去噪算法.算法将测量中不同背景光强下所得测量值的平均值之差作为补偿系数,通过补偿系数消除动态背景噪声对压缩感知成像系统的非线性影响.仿真结果表明, 在总数为900次的采样过程中, 背影噪声动态变化300次时,算法能够将重建图像的峰值信噪比由29.5 dB提高到62 dB；在动态背景噪声的影响下, 本文算法能够大大提高目标图像的可读性, 提高成像质量, 增加压缩感知成像系统的鲁棒性.

A algorithm which uses the compensation factor to eliminate nonlinear errors was proposed to reduce the nonlinear errors caused by sudden change of background in the imaging system based on compressed sensing. The compensation factor was calculated from the mean value of measured data under different background. The simulation results show that the proposed algorithm improve the peak signal to noise ratio of reconstructed image from 29.5 dB to 62 dB when the background noise change as many as 300 times during 900 times sampling. The reconstructed image is more readable and the imaging system is more robust with the proposed algorithm.