Quantitative study on a resampling mask method for speckle reduction with amplitude superposition.

One-shot digital holographic imaging has the advantages of high stability and low temporal cost. However, its reconstruction is degraded severely by the laser speckle. A rectangle, ellipse, and diamond resampling mask method in spatial domain for speckle reduction is proposed. The effectiveness of the method for speckle reduction is explained successfully. In the method, one hologram recorded in a certain size is divided into N=S×T sub-holograms. Angular spectrum transform is applied to the holographic reconstruction of a diffuse object. N reconstructed amplitude images are calculated from the corresponding sub-holograms. Benefitting from speckle's random distribution, superimposing these N uncorrelated amplitude images would lead to a final reconstructed image with reduced speckle. Normalized relative standard deviation values of the reconstructed image are in good agreement with the asymptotical law. The maximum relative errors between the experiment data and the theoretical values are below 7.2%. The effect of the method on the spatial resolution of the reconstructed image is also quantitatively evaluated. Experimental and simulation results prove the feasibility and effectiveness of the proposed method.