Non-line-of-sight imaging algorithm based on Wiener filtering of mid-frequency

Non-line-of-sight (NLOS) imaging is an emerging technology for optical imaging of objects blocked out of the detector's line of sight. Non-line-of-sight imaging based on light-cone transform and inverted method can be regarded as a deconvolution process. The traditional wiener filtering deconvolution method uses empirical values or repeated attempts to obtain the power spectral density noise-to-signal ratio (PSDNSR) of the transient image which is different in various hidden scenes of NLOS imaging, so the prior estimation is not appropriate and repeated attempts make it difficult to quickly find the optimal value. Therefore, this paper proposes a method which estimate PSDNSR using the mid-frequency information of captured transient images for wiener filtering to achieve NLOS imaging. In this method, the turning points between the mid-frequency domain and the high-frequency domain of the transient image amplitude spectrum are determined, and then the PSDNSR value is solved by analyzing the characteristics and relationship of the noise power spectrum in the low, middle and high frequency. Experiments show that PSDNSR estimated by NLOS imaging algorithm based on wiener filtering of mid-frequency domain is of the order of magnitude with better reconstruction effect. Compared with other methods, the algorithm in this paper can directly estimate PSDNSR in one step, without iterative operation, and the computational complexity is low, which simplifies the parameter adjustment steps of the Wiener filtering deconvolution Non-line-of-sight imaging algorithm based on light-cone transform, so that the reconstruction efficiency can be improved on the premise of ensuring the reconstruction effect.