Abstract

We report a novel and fast method for converting a digital, complex Fresnel hologram into a phase-only hologram. Briefly, the pixels in the complex hologram are scanned sequentially in a row by row manner. The odd and even rows are scanned from opposite directions, constituting to a bidirectional error diffusion process. The magnitude of each visited pixel is forced to be a constant value, while preserving the exact phase value. The resulting error is diffused to the neighboring pixels that have not been visited before. The resulting novel phase-only hologram is called the bidirectional error diffusion (BERD) hologram. The reconstructed image from the BERD hologram exhibits high fidelity as compared with those obtained with the original complex hologram.

Highlights

  • Computer-generated holography (CGH) has undergone encouraging development in the past two decades

  • We report a novel and fast method for converting a digital, complex Fresnel hologram into a phase-only hologram

  • The odd and even rows are scanned from opposite directions, constituting to a bidirectional error diffusion process

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Summary

Introduction

Computer-generated holography (CGH) has undergone encouraging development in the past two decades. The pair of SLMs is replaced by a single device, displaying a pair of holograms and subsequently merging the reconstructed wavefront through a grating [7,8,9,10] Such approach is effective, the optical setups are rather complicated. On the downside, removing the magnitude component will lead to heavy distortion on the reconstructed image To alleviate this problem, the Gerberg-Saxton algorithm [11], or iterative Fresnel transform [12] are often adopted to compute the phase hologram in an iterative manner, so that the reconstructed image will match with a target planar image. Different from the OSPR scheme, or other iterative approaches that generate a phase-only hologram from an object scene, our proposed method can be applied directly on a given digital complex hologram

Basic approach based on unidirectional error diffusion
Enhanced method based on bidirectional error diffusion process
Experimental results
Conclusion

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