基于压缩感知的动态散射成像

利用基于压缩感知的成像系统可以透过静态的散射介质获得高质量的重建图像. 但是当散射介质动态变化时, 因为采样所得的测量值受到散射介质衰减系数非线性变化的影响, 重建图像质量会大大下降. 针对上述情况, 本文提出基于压缩感知成像系统的测量值线性拉伸算法, 该算法能够对所得到的非线性测量值进行分析, 根据测量值大小的不同将测量值划分成数个区域并计算补偿系数, 从而根据补偿系数进行测量值线性拉伸变换, 使测量值线性化. 最后再对变换后的测量值进行压缩感知重建计算. 通过理论分析、计算机仿真和实验证明了所提算法能够有效地应对动态的散射介质, 提高基于压缩感知成像系统在透过动态散射介质时的图像重建质量.

Imaging through dynamic scattering media with compressed sensing

Imaging through scattering media has been a focus in research because of its meaningful applications in many fields. Recently, it has been proposed that high quality images can be recovered after passing through stationary scattering media by using the single-pixel imaging system based on compressed sensing. No doubt, it is a very interesting discovery about compressed sensing. However, it is also reported that high quality image can be recovered only with stationary scattering media. Mostly, the scattering media will not remain stationary, for example, the properties of the fog will be dynamically changed when their is wind. Thus, in a dynamic case, the transmittance of the scattering media will be nonlinear over the time, which will make the measured data nonlinear and the reconstructed image quality decrease. In this paper, a novel algorithm of linear transformation for measured data (LTMD) is proposed to make the nonlinear attenuation factor gain a linear transformation after passing through the dynamic scattering media. The factor ξ is proposed from the theoretical calculus based on compressed sensing, and this correction factor ξ can help to eliminate the nonlinear errors caused by dynamic scattering media and make the measured data linear. So the transformed data will greatly upgrade the reconstructed image quality. Simulation results show that high peak singnal to noise ratio images can still be recovered even when the dynamic frequency reaches 300 times in the 900 times of sampling. In experiments, plastic films are used as scattering media, and the number of films can be changed during the sampling to simulate the dynamic state of scattering media. With LTMD, high quality image with a resolution of 64× 48 is recovered after passing through dynamic plastic films while the recovered result without LTMD is still hard to be distinguished. The traditional reconstructed algorithms orthogonal matching pursuit, Tval3 and L1-magic are also used in the experiments, and the image is still hard to recover with any of the three traditional algorithms. In a word, the proposed LTMD algorithm uses the correction factor ξ to make the affected nonlinear-measured data linear, so as to increase the reconstructed quality of the imaging system based on the compressed sensing even when passing through scattering media with highly dynamic frequency.