Compensating spatial information loss caused by dynamic eye pupil sampling in holographic near-eye displays via...

In holographic near-eye displays, dynamic eye pupil sampling causes spatial information loss, which leads to low quality of the observed holographic image. To address this, we propose a hologram optimization method that combines time multiplexing with random pupil mask sampling. First, the time multiplexing was incorporated into the hologram optimization and reconstruction processes, thereby enabling compensation of missing spatial information from the time dimension. Second, 1,000 randomly generated pupil masks were integrated into the optimization algorithm of the hologram to adapt to the dynamic changes of the eye pupil. To ensure more uniform holographic image quality under dynamic pupil variations, the pupil masks were sorted in descending order of diameter during the iterative process. Simulations and experiments show that the proposed method can effectively compensate for the loss of spatial information caused by pupil sampling. Moreover, when the pupil dynamically changes, a more uniform holographic image quality can be observed.