Scattering imaging based on the phase retrieval algorithm of an adaptive partitioned support domain

To address the issue of iterative stagnation caused by twin-image artifacts in conventional phase retrieval methods based on global support constraints, an adaptive partitioned support constraint (APS) of the phase retrieval algorithm utilizing a discrimination of correlation coefficient threshold is proposed in this paper. The algorithm calculates the correlation coefficient δ between the Fourier amplitude obtained through iterative updates and the target Fourier amplitude obtained from the speckle autocorrelation. When the correlation coefficient δ is below the presupposed threshold, the processing mechanism of support constraint divided into two pieces is automatically triggered. Numerical simulations demonstrate that, compared to conventional methods, the phase retrieval algorithm of adaptive partitioned support constraint dramatically mitigates the impact of twin images, showing advantages by both the sum-squared error (SSE) and the image universal quality index (UQI) evaluation metrics. The phase retrieval algorithm of adaptive partitioned support constraint mitigates the interference of twin images during the iteration process, providing new, to our knowledge, insights into the speckle autocorrelation imaging and promoting practical applications of scattering imaging technology in fields such as biomedicine and deep-sea exploration. Furthermore, this algorithm can be combined with X-ray imaging and Fourier ptychographic microscopy (FPM) technology to reduce imaging time and improve imaging quality.