Adaptive weighted Gerchberg-Saxton algorithm for generation of phase-only hologram with artifacts suppression

Yang Wu, Jun Wang, Chun Chen, Chan-Juan Liu, Feng-Ming Jin, Ni Chen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In the conventional weighted Gerchberg-Saxton (GS) algorithm, the feedback is used to accelerate the convergence. However, it will lead to the iteration divergence. To solve this issue, an adaptive weighted GS algorithm is proposed in this paper. By replacing the conventional feedback with our designed feedback, the convergence can be ensured in the proposed method. Compared with the traditional GS iteration method, the proposed method improves the peak signal-noise ratio of the reconstructed image with 4.8 dB on average. Moreover, an approximate quadratic phase is proposed to suppress the artifacts in optical reconstruction. Therefore, a high-quality image can be reconstructed without the artifacts in our designed Argument Reality device. Both numerical simulations and optical experiments have validated the effectiveness of the proposed method.
Original languageEnglish (US)
Pages (from-to)1412
JournalOptics Express
Volume29
Issue number2
DOIs
StatePublished - Jan 8 2021

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