Phase-only hologram optimization with adaptive constraint strategy for high-quality optical reconstruction

Aiming to address problems of unstable convergence and poor reconstruction quality of traditional iterative algorithms, an adaptive constrained iterative algorithm based on angular-spectrum propagation is proposed. A set of discrete plane waves, which is computed to approximate the quadratic phase, is used to suppress scattering noise and artifacts due to the power of convergence of light rays of the quadratic phase. The target plane is divided into signal and non-signal areas. The corresponding adaptive amplitude constraints and bandwidth constraints strategies are applied to different areas during the iteration process. The iteration process is adjusted by setting the adaptive feedback coefficients to optimize the iteration step size in order to achieve stable and fast convergence. After 200 iterations, the algorithm has converged, and compared to traditional algorithms, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) are improved by 10.1 dB and 0.19, respectively. The experimental results show that the reconstructed images have less noise and higher reconstruction quality, and verify the effectiveness of the proposed method.