Comparison of four deblurring methods for streak image of streak tube imaging lidar

In this study, the Richardson-Lucy (R-L) iteration, Tikhonov (T-K) regularization, and fast iterative shrinkage-thresholding algorithm (FISTA) are first used to deblur streak images. The deblur performances of these three methods are compared with that ofWiener deconvolution. The spatial resolutions of Wiener deconvolution, R-L iteration, T-K regularization, and FISTA improved from 9 mm to 4.5, 5, 5, and 5 mm, respectively. The root-mean-square errors (RMSE) of one -, two -, and three-plane targets decreased effectively using these three deblur methods. The R-L iteration performs the best in terms of the RMSE for the two-plane target. The effects of the parameters used in each method are investigated.