Reconstructing targets based on the enhancement of speckle patterns with the hybrid input-output algorithm

Recovering the object hidden in the disorganized speckle pattern generated through diffusive materials is an important topic as well as a difficult challenge. Existing speckle correlation imaging approaches generally use the speckle autocorrelation to extract the Fourier amplitude information of the target. Our goal here is to research the effects of the quality of the speckle autocorrelation on reconstructing targets via the HIO-ER (hybrid input-output and the error reduction) algorithm. Specifically, a low-quality speckle pattern is preprocessed to estimate a high-quality autocorrelation. The PSNR of the preprocessed autocorrelation could be increased from 5.88 dB to 24.08 dB. The results of preprocessed and unprocessed reconstructions are compared, and the quality of reconstructions could be significantly improved than the later one. The results indicate that a high-quality speckle autocorrelation obtained by the preprocessing helps to optimize reconstructing targets.