Noise Impact Analysis in Computer-Generated Holography Based on Dual Metrics Evaluation via Peak Signal-to-Noise Ratio and Structural Similarity Index Measure

Abstract

This study investigates the noise impact on reconstructed images in computer-generated holography (CGH) through theoretical analysis and Matlab 2015b simulations. By quantitatively injecting noise to mimic practical interference environments, we systematically analyze the degradation mechanisms of four CGH types: detour-phase, modified off-axis beam reference, kinoform, and interference type. A dual-metric evaluation framework combining peak signal-to-noise ratio (PSNR) and the Structural Similarity Index Measure (SSIM) is proposed. Results demonstrate that increasing noise intensity induces progressive declines in reconstruction quality, manifested as PSNR reduction and SSIM-based structural fidelity loss. The findings provide theoretical guidance for noise suppression, parameter optimization, and algorithm selection in CGH systems, advancing its applications in optical encryption and high-precision imaging.